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101 Careers in Mathematics Fourth Edition

AMS / MAA

CLASSROOM RESOURCE MATERIALS

VOL 64

101 Careers in Mathematics Fourth Edition Deanna Haunsperger Robert Thompson Editors

Providence, Rhode Island

Classroom Resource Materials Editorial Board Cynthia J. Huffman, Editor Jayadev Siddhanta Athreya Haseeb A. Kazi Bret J. Benesh Tamara J. Lakins Cristina Eubanks-Turner Jessica M. Libertini Joel K. Haack Brian Lins Christopher Hallstrom Darryl Yong Brian Paul Katz 2010 Mathematics Subject Classification. Primary 00-XX, 01-XX, 97-XX.

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24 23 22 21 20 19

Contents Introduction

xi

Charlotte Abrams

1

Xiaoling (Ling Ling) Lim Ang

3

Noelle Balandi

5

Brian T. Bares

7

Paige Bartholomew

9

Ben Baumer

11

Stacy Beaudoin

13

Ebonii Bell

15

Robert M. Bell

17

Nicholas Bennett

19

Nicole Bertram

21

Toni Bluher

23

Kate Brady

25

Marina Brockway

27

Sarah Brown

29

Lisa Byrne

31

Jenna P. Carpenter

33

Tim Chartier

35

Bill Correll, Jr.

37

Carla Cotwright-Williams

39

Mimi Cukier

41

Michael Dairyko

43

Kathleen Daly

45 v

vi

CONTENTS

Joshua R. Davis

47

Erick Deras

49

Lizette Ortega Dickey

51

Alyson Doles

53

Samantha Drost

55

Kate Dyson

57

Berton Earnshaw

59

Chandra Erdman

61

Katie Evans

63

Jaquelyn Fernandez Rieke

65

Stephanie Fitchett

67

Kathie Flood

69

Tamara Fuenzalida

71

Angela Gallant

73

Skip Garibaldi

75

Sommer Gentry

77

Jennika Gold Thomas

79

Amanda (Quiring) Gonzales

81

Amanda Hanford

83

Harold Hausman

85

Ebony Hitch

87

Kelly Hobson

89

Marylesa Howard

91

Rachel Insoft

93

Eleisha Jackson

95

RDML (Ret) “CJ” Jaynes

97

Maribeth Johnson

99

Marina Johnson

101

Erin Jones

103

CONTENTS

vii

Barbara Jordan

105

Harlan Kadish

107

David Keyes

109

Stacey Faulkenberg Larsen

111

Dan Loeb

113

Aaron Luttman

115

Dana Mackenzie

117

Chad Magers

119

Alex McAdams

121

Carissa Mendoza

123

Carol Meyers

125

Erika Meza

127

Christopher Minck

129

George Mohler

131

David Moore

133

Tanya Moore

135

Walter Morales

137

Janeth Moran-Cervantes

139

Elizabeth Morgan

141

Carol Muehrcke

143

Grace Nabholz

145

Aisha N´ ajera Chesler

147

Andy Niedermaier

149

Jacqueline Nolis

151

Kyle Novak

155

Dean Oliver

157

Laurel Paget-Seekins

159

Christine Papai

161

Yolanda Parker

163

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CONTENTS

Karoline Pershell

165

Cara D. Petonic

167

Jacqueline Pfadt

169

Ashley Pitlyk

171

Kimberly Plesnicar

173

Amanda Plunkett

175

Elizabeth Pontius

177

Emilie Purvine

179

Gregory Rae

181

Rachel Ramirez

183

Blake Rector

185

Mary Lynn Reed

187

Adam L. Rich

189

Christina Roberts

191

Shannon Rogers

193

Lucas Sabalka

195

Jeffrey Saltzman

197

Bonita V. Saunders

199

Kayli Schafer

201

Jeanette Shakalli

203

Julie Shapiro

205

Ali Shappy

207

Richard Sharp

209

Danielle Shepherd

211

Benjamin P. Simmons

213

Andrew Stein

215

Jean Steiner

217

Courtney Stephens

219

Sumanth Swaminathan

221

CONTENTS

ix

Rebecca Swanson

223

Shree Taylor

225

Alec Torigian

227

Robert Troy

229

Jane Turnbull

231

Jasmin Uribe

233

Liz Uribe

235

Kim Van Duzer

237

Andrea Walker

239

Clemmie B. Whatley

241

Beatrice White

243

Chris Wiggins

245

Bryan Williams

247

Donald C. Williams

249

Joyce Yen

251

Starting your job search

253

Preparing for an interview

257

Applying to graduate school

261

Contents by career area

265

Contents by highest degree earned

277

Introduction This is the decade in which the President’s Council of Advisors on Science and Technology recommended increasing the number of STEM graduates by one million to meet projected employment needs. Yet we rarely see a job title of “mathematician.” Why is that? Because mathematicians can do anything. In this book you’ll encounter mathematicians with job titles ranging from Senior Data Scientist to Senior Bicycle Planner, from Pilot to President and CEO. A degree in mathematics does not just knock upon the doors of business and industry; it flings them wide open. Mathematicians are valued by their employers for their logical reasoning, clear communication, and their ability to teach themselves anything they need to know. A degree in mathematics shows that its holder has grit and determination, is able to analyze and synthesize information, and doesn’t back down from a challenge. We are problem-solvers and hard workers. We are adaptable and versatile. We are the workforce of tomorrow whom businesses and government seek. If you are a high school student, use this book to get inspired. Read profiles and talk to your teachers and your counselors about opportunities to learn and do more mathematics. Pursue a mathematical activity that challenges and excites you. You could solve recreational problems, code up a neat algorithm, volunteer to tutor math to other students, or even apply to a summer math camp. If you are a college student, use this book to explore your interests. Read profiles and find careers that sound like they fit your strengths and your values. Read the essay “Starting your job search” in the back of this book. Talk to your professors about careers and ask what kinds of jobs previous students have pursued. Talk to your career center about internships and use your school’s resources to help with your job search and resume and interview preparation. If you are a teacher, don’t let this book gather dust on your shelf! Put it in a spot where students congregate so they can peruse it. Bring a career profile to class and show your students the interesting things you can do with a degree in math. Our appreciation goes to Andrew Sterrett for allowing us to edit this new fourth edition of 101 Careers in Mathematics. This book was Andy’s brainchild; it has provided generations of students with many answers to the enduring question: “What can I do with a degree in mathematics?” We hope this new edition will be just as useful to another generation of mathematics students and educators. For more career resources, check out the career information websites from the Mathematical Association of America (mathcareers.maa.org) and the American Mathematical Society (www.ams.org/profession/career-info/career-index) and the Society for Industrial and Applied Mathematics’s new book, BIG Jobs Guide. Deanna Haunsperger and Rob Thompson xi

Charlotte Abrams

Graduate Student Columbia University Willamette University BA Mathematics Columbia University MPH Biostatistics

“Cure Cancer with Data Science.” This was the writing on a billboard I passed every day on my way to work, two years after I graduated from college. These words led me to where I am today, a graduate student well on the way to a Master’s degree in Public Health. The journey has been long and winding, but I wouldn’t have changed it one bit. When I first began my undergraduate education at Willamette University, I felt unsure about my future. I excelled in math in high school and knew I enjoyed it, but I wasn’t thinking about math as a major. After taking several classes in the math department and getting to know the professors, I realized that mathematics was a good match for me. But I still had no clue where I wanted the degree to take me. I knew, and was constantly being told, that math majors were in high demand in the workforce, and I wouldn’t have a problem finding a job after school. Unfortunately, I hadn’t found a career path I was passionate about yet, and that made it difficult to relate my degree to a future career. As I moved into upper-class study, the courses began to deviate from what I’d previously known and considered as “math.” I remember being extremely confused in my first proof writing class, thinking it had absolutely nothing to do with the calculus I’d learned in high school and college. From there, it just got more abstract. While learning about the theorems and proofs that underly fundamental mathematics was interesting, I wanted to learn concepts more clearly applicable to the real world. This made career planning even more complicated because most of my courses leading up to graduation were heavily theory focused. I left college somewhat confused as to how I would incorporate math into my life, so I took some 1

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time to figure it out. I started by spending a year teaching English to children in Vigo, Spain. This amazing experience allowed me to realize how much I enjoy helping other people. After returning to the US, I attended a coding boot camp and was subsequently hired by a virtual healthcare company in Seattle as a web developer. I went into this job with very basic programming skills, but thanks to some patient mentorship from co-workers, the transition was easy. I can’t say writing proofs directly helped me with this job, but studying math in school taught me to be a better problem solver and to approach problems in a unique way – attributes certainly needed by good web developers. The job made me see that math is used everywhere: in computer programming, in weather prediction, in calculating traffic flows, in the placement of items in grocery stores, the list goes on. It wasn’t all research and theory. I definitely needed those years after college to better understand my love for math. I truly had no idea what I wanted when I graduated, and that was completely fine. I used the next two years to take a step back, figure out what was meaningful to me, and realize that math had to be a core component of my career. Inspired, I applied and was accepted into the graduate program in Biostatistics at Columbia University, which is where I am currently. This program allows me to incorporate my desire to help people with my love of the application side of math. In the past, graduates from this program have found careers in data analytics, biostatistics, and – where I hope to be after graduation – data science. I’m excited to see where the program will take me. Even though it took me a little time to get to where I am now, my background in math has been an indispensable tool for me along the way. It has allowed me to hone the problem-solving skills which are fundamental not only to most jobs, but also essential on a day-to-day basis.

Xiaoling (Ling Ling) Lim Ang

Associate Director NERA Economic Consulting Loyola University Chicago BS Mathematics, Economics Minor MS Mathematics Princeton University MA Economics PhD Economics

I currently work as Associate Director at NERA Economic Consulting. We work with world-class law firms and Fortune 500 companies to provide sound economic, financial and quantitative analysis in legal disputes and a variety of business matters. This involves a fair bit of econometrics, which is exactly what it sounds like: the application of economics and statistics to real-world problems. When I was in college, I was interested in a range of areas, and was drawn to mathematics for its elegance, and to social science because of how it applies rigor to explain human behavior. In my current role, I do a little bit of both, and need to make sure that I can explain economic analyses to lawyers and judges who do not necessarily have training in math and economics. I was fortunate to have a broad liberal arts education that taught me the different ways that people think rigorously and also how to write and communicate complicated ideas to people with different backgrounds. Class discussions in classes like philosophy and political science with classmates who do not think as linearly as other math majors, and working as a math and economics teaching assistant and tutor helped me learn how different people process math concepts. I had the opportunity to testify at a trial recently, and preparing for that really made me check my use of jargon! In my day-to-day work I use a lot of math, including statistics, probability theory, calculus, and real analysis, while also working through the narrative of the project. I also code or supervise others who code in statistical languages like Stata or SAS. Although I’m usually working on the analysis for an expert report or client deliverable when I’m at work, the tasks involved can differ greatly. We work in teams that can range from three people to a dozen at my firm, in addition to a 3

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XIAOLING (LING LING) LIM ANG

team of lawyers at a law firm. I serve in a management role on projects that can take months or years, which means that I have to understand the arc of the project as well as what has been done and what needs to get done as the project evolves. My role includes working with senior colleagues to figure out what questions need to be asked, how to request data and understand the data we receive, and how to perform the analysis. In a litigation context, there is typically an opposing expert, and we need to take into account his or her analysis. In fact, we receive something called “turnover” which consists of all of the programs and analysis produced by the opposing expert. When we receive turnover, we have a limited amount of time to go through these programs and understand what was done and respond appropriately. At all levels this work is highly collaborative and precise – we double check everything we do and bounce ideas off of each other. When you know that what you’re doing is going to be scrutinized, you have to be extra careful, but precision is not a foreign concept to a math major! I found my way into this career by keeping up to date with what was going on in my field and related areas. I studied labor economics in graduate school (e.g. unemployment, education, etc.), but decided to start my career at financial services regulators – the Consumer Financial Protection Bureau and the Federal Deposit Insurance Corporation – since I graduated during the Financial Crisis and wanted to learn more about the financial sector. My educational background has been a flexible toolkit that applies in many contexts. Of course, tools can get rusty, so I try to keep up with new developments – both in terms of legal precedent and economic research and techniques. I find that staying active by attending and presenting at conferences, trainings, and seminars and by talking to people who work on different but related things is a great way to develop professionally. When I was younger, the concept of networking seemed so awkward and against my introverted nature, but now that I’ve been out of school for a while, it seems like a natural way to learn. This job is hectic and involves long hours, but I feel like I’m always learning.

Noelle Balandi

Finance Specialist Multnomah County, Oregon Lewis & Clark College BA Economics and Mathematics Portland State University MS Financial Analysis

I came to the US in 2010 on an F-1 visa to pursue my undergraduate degree at Lewis & Clark College. I did not have an internship while I was attending college; however, I did have internships in London, UK, during my study abroad program and in Ouagadougou, Burkina Faso, during my summers at home. International students on an F-1 visa in the US have the option of staying in the US to work after successfully graduating college. They are given a one-year temporary work permit known as Optional Practical Training. I chose to stay in the US and find a job. Finding a job was very difficult since I was very restricted by my work permit. The restriction was to work within the field of my major. Because all my internships were in the humanitarian field, it was very difficult finding a job in a different field without having experience. I volunteered and continued networking until I got very lucky and found a job as a finance specialist in Multnomah County, Oregon, in the Health Department. A normal day at work is an eight-hour shift during which I process between 50 to 300 invoices through SAP (a finance software program), have meetings, and prepare reports. I don’t take work home, and I love that. I have no homework and no assignments to turn in. Therefore, I have a lot of time after work to spend with my family and friends. My team consists of five people. We all work in the Health Department/Business Operations under Mental Health. We work independently, with weekly team meetings and one-on-one meetings with our manager. English is my fourth language. I started learning English three years prior to moving to the US in 2010. After I arrived at Lewis & Clark, I just found myself studying mathematics. Unlike my other classes, I really enjoyed being in a math 5

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class because my English was not judged, and I did not have to write essays. All I had to do was to solve problems. I was very inspired by my math professors because they always made the classes very fun. I did not feel intimidated to speak up in class. Although the classes got harder, I really enjoyed most of my mathematics classes and wanted to take on the challenges. Multivariable Calculus was my favorite class with the introduction to three-dimensional images; I loved drawing spheres and imagining the rotations. My mathematics degree helps me in my daily life when it comes to making decisions. My problem solving skills helped me tremendously when I was training to use SAP. It was much easier for me to organize my reports and run them. It helped being a fast and successful learner within the finance field. I later obtained my Masters in Financial Analysis because I really enjoyed what I was doing. The classes in mathematics that have helped me most with my job are my statistics classes; they are the most practical because I find myself using these skills on a daily basis. I know how to run a pivot table, how to draw graphs, etc. The advice I would give someone who wants my job is to be very active when job searching, and voice what you see yourself doing. I did not know that I wanted to be a finance specialist. I later realized that it is important to know what kind of environment you want to work in and if there is potential for growth. Networking is everything. There is always someone who knows someone who can give you an opportunity. If I could go back in time, I would get an internship in the US; not only is it easier to translate on a resume, but it also allows you to build relationships with people, and that internship can turn into something permanent. I recently returned to being a full-time student at Portland State University taking prerequisite classes with the intention of continuing further studies in medicine. You never know where math is going to take you!

Brian T. Bares

Founder and Chief Investment Officer Bares Capital Management, Inc. University of Nebraska–Lincoln BS Mathematics Chartered Financial Analyst

Completing a challenging undergraduate degree like mathematics armed me with the confidence that I could tackle intellectually difficult problems. It also required me to drill down deeply in certain areas, something that is required of people as they move into new areas with increasing responsibility. I have always been interested in business, even from a young age. My early experience in stock market investing as a teenager normally would have pushed someone with my interests into finance or business as an undergraduate, but two complementary forces pushed me into mathematics. First, I had an aptitude for mathematics at a young age, and I viewed a degree in math as a challenging and stimulating endeavor. Second, the University of Nebraska–Lincoln selected me to be included in its honors math program, which allowed me to experience smaller class sizes taught directly by professors. I enrolled in a course that used Stephen Kellison’s book “The Theory of Interest,” which explained the underlying mathematics of compound interest and annuities. This course, coupled with some actuarial science courses that were cross-listed with the math department, gave me a strong mathematical foundation for work in finance and investments. The expected path for me upon graduation was to take an actuarial job, but I knew that my entrepreneurial ambition and intense interest in investing would lead me down an unconventional path. I decided to relocate to Austin, Texas, and performed a comprehensive review of investment management firms there. I met with as many of them as I could with a “cold approach” offer of working for free until I could become a valuable team member. I hit it off with an investment manager in the early stages of the firm’s life cycle. I was hired for no pay and began 7

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what became an intense three-year apprenticeship. As my value to the organization grew, I was salaried at levels commensurate with my experience. I was lucky enough to see the growth of a small investment boutique as it raised assets from individuals and institutions through multiple channels. After a few years, I decided to put some ideas I had been thinking about into practice for myself. I started Bares Capital Management from the spare bedroom of my condo in Austin in June of 2000 with a laptop and some portfolio accounting software. Our organization now manages over $3.4 billion in client assets. I founded my institutional investment management company on the premise that concentrated portfolios of carefully researched and selected common stocks could outperform market benchmarks. I lead a team of eleven research professionals who perform in-depth analysis on common stocks. We focus our efforts on evaluation of a company’s competitive positioning, management expertise and incentives, and potential for growth. Our team is known for its extensive fieldwork. We focus our efforts on companies that score highly on qualitative evaluation before undertaking quantitative valuation and appraisal work. Our portfolios are created to give our clients the highest expected returns. My mathematics training has reinforced for me the concept that compound interest truly is, as Einstein (may have) famously quipped, “the eighth wonder of the world.” Understanding the relatively straightforward math of how capital can be accumulated or destroyed is a cornerstone skill. If a mathematics major wants to pursue a more non-traditional career path, I would recommend that the student begins to network early on with people in whatever field generates the most intense interest. Making a “cold approach” like I did can sometimes be effective, but expectations must be that money and responsibility will come much later. The priority should be to gain practical experience in the given field and then to become invaluable to your organization. Only then will the deeper skills that come with a mathematics degree help to accelerate success.

Paige Bartholomew

Consultant Bain & Company Brigham Young University BS Mathematics

I am a management consultant. Management consultants are hired by other companies to solve their most challenging problems, whether that be defining a ten-year business strategy, cutting costs, or predicting market conditions in five years (all projects I have been a part of). I work for Bain & Company, one of the top management consulting firms in the world, and ranked the #1 place to work in 2017. About every three months, I am staffed on a new project for a new client. This means I am introduced to a new industry, new manager, and new work location multiple times a year! Consulting combines problem-solving, analytical skills, and people skills in a fast-paced and ever-changing work environment. As I neared graduation, I started looking into jobs related to business. I soon discovered consulting from some of my friends in business majors. Bain & Company immediately stood out to me. Bain did not care that I did not have a business degree; Bain valued my math skills and promised to teach me the business knowledge I needed to be successful. I was also drawn to Bain’s project-based work, knowing that my job would change every three months when staffed to a new project. I knew that there was no better way to experiment and find out what types of jobs I liked right out of school. Bain & Company recognizes that the study of mathematics is really the study of problem solving. And they need people to help them solve hard problems! The patience and creativity in problem solving I used as I tried to prove mathematical theorems are the same skills that I draw on in my day-to-day life at Bain. Management consulting also frequently uses data analytics; all of my managers have had complete confidence in my analytical skills because they knew I came from a quantitative background. 9

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A normal day at Bain is filled with internal team meetings, client meetings, data analytics, creating presentations, and lots of hanging out with my team! I usually work about twelve hours a day, but the days fly by because there’s so much to do. I love the fast pace, the opportunity to work with people much more senior than me, and the opportunity to influence the decisions of some of the biggest companies in the world, even though I have barely graduated! At Bain we work in teams, and therefore spend a lot of time together. When we work at our clients’ offices, we all sit in one team room together, including partners, managers, and consultants. This can occasionally make it difficult to concentrate, but the upside is that you always know the big picture of the work you are doing. My coworkers have become some of my best friends as we have worked and traveled all over the world together. One of my recent projects at Bain was to forecast market conditions for cell phone plans over the next five years for a large telecommunications company. I built a model that took into account the number of cell phone users in the US, cell phone plan prices, data usage by phone, cell tower infrastructure costs, and many more data points, to then output market conditions in 2021. It was a huge and complicated Excel model that required attention to detail, a thorough understanding of statistics, and a lot of trial and error. My background in math gave me the confidence to build such a complicated model even though I previously knew nothing about the telecommunications industry! I travel for work wherever our clients’ offices are located. In the last three years I have worked in Arizona, Arkansas, Texas, Florida, and even Belgium! Every Monday morning I hop on a flight to the client, and every Thursday evening I fly back to Dallas where the Bain office is located. Everyone at Bain works in their local office on Fridays; my local office is Dallas but there are offices all over the world. Even though I usually work an average of 60 hours per week, I am always able to relax and recharge on the weekends. My career advice? Get good grades! The top management consulting firms want to see that you can handle the pressures of school and still come out on top. It’s also important to demonstrate leadership and have some previous work experience, so don’t be afraid to volunteer in a campus club or get a summer internship. Bain & Company is a great place to work, especially for math majors interested in pursuing a career in business.

Ben Baumer Assistant Professor Statistical and Data Sciences Smith College Statistical Analyst New York Mets (2004-2012) Wesleyan University BA Economics University of California, San Diego MA Applied Mathematics Graduate Center City University of New York PhD Mathematics

I am a data scientist. Data science is an emerging field commonly described as “the practice of deriving valuable insights from data,” and this thread runs through all of my work. I’ll discuss my work before I began teaching at Smith College, when I served as a Statistical Analyst for the New York Mets. My work in the baseball operations department and my job had two main components. First, advising the general manager and assistant general manager on player evaluation at all levels. This includes both major and minor league players who may already be within the organization or who might be available through trades and free agency. Second, managing and developing a baseball information system, which consists of an internal website and back-end database. This system is used to deliver statistical information to the front office as well as the field staff, trainers, and scouting personnel. I was very lucky to get involved in this job. I finished my master’s in applied math in the spring of 2003, which was right around the time that “Moneyball” came out. That book opened the door for statistical analysts in professional sports, and I was informed through a personal connection that the Mets were looking to hire someone for that role. I don’t think they knew exactly what they were looking for, but I must have been the right combination of young and capable. I had also been a Mets fan my entire life and had played baseball at the high school varsity level, and I don’t think those factors hurt either. The front office personnel typically work a normal 9:30-5:30 day in the office. However, during the season, my colleagues and I would stay for all of the home 11

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games. Games don’t usually end until 10:00 at the earliest, and during a home stand six of those in a row (including weekends) are normally played. So about half of the summer weeks would stretch into the 70-80 hour range. When the team was away and during the off-season the hours would be more regular, but special events like the Winter Meetings or the trade deadline required more time. Most of the time, I worked in an office environment in the ballpark, but during the games I was usually able to find a seat and watch the game. Because of the nature of the work, I spent a lot of time writing code, but many of the projects I worked on were collaborative. Of course we had many meetings and input from many different people was solicited before we made any major decisions. There is no way I would have been hired without my master’s degree in applied mathematics; it was absolutely essential to being able to do high-quality work in sports analytics. Many people wanted my job, but having a graduate degree definitely put me in a different category. Mathematics informs the statistical models that allow us to fit smooth surfaces to what are otherwise irregular distributions. For example, the true extent of a shortstop’s range is obviously smooth due to physical properties of human beings, but the observations we have about that range are inherently discrete. Through statistics we can reconcile these two conceptions of reality. Later, as I progressed through my PhD program, the complexity of the models I was able to understand and implement only grew. Even though I didn’t write a lot of mathematics for my job, a solid foundation was integral to almost everything that I did. What’s my advice for someone wanting a job like this? Learn as much as you can about statistical modeling, and make sure that you are fluent in a statistical computing language like R or Python. Understanding databases and writing SQL queries is also a must. Equally important is to have an understanding and appreciation for the non-statistical aspects of the game. Learn about scouting, as that knowledge will help you understand what statistical questions are interesting and relevant. Always stay open to new ideas!

Stacy Beaudoin

Math Teacher St. Paul’s School Bowdoin College BA Mathematics and Psychology University of New Hampshire MST Mathematics

Ever since high school, I’ve wanted to become a math teacher. I loved the subject and enjoyed learning and felt that it would be the perfect career for me. In college, I majored in math and minored in education to prepare myself for this career. I also took advantage of summer internships at boarding schools to get a taste of what it was like to be a teacher in that environment. Now I teach high school mathematics at a boarding school. I am also a coach and an adviser. One thing I love about teaching is that there is always something different happening! Whether it be a change in schedule, a new class to teach, a group of students who solve a problem in a different way, each day is never exactly like the next. This keeps things fresh and exciting! But, in general, on a typical day, I head to chapel at 8:00 a.m., then teach anywhere from 2 to 4 classes and attend meetings until roughly 3:00 p.m., then head off to sports. At night, I may have a sit-down dinner, dorm duty, or extra help. My job is very collaborative. We work in teaching teams to plan our courses throughout the year, and I will often check in informally with colleagues throughout the year to get advice or feedback. Then, day to day, I’m always interacting with students and other members of the community. Since I teach mathematics, I use math every day. I have to have a solid command over the subject matter in order to be a successful teacher. My degree in mathematics has given me that. However, one might argue that most of the math courses I took in college are way beyond the math that I teach on a day to day basis. And while some of that may be true, knowing what math lies ahead helps me to emphasize to my students what is most important to know. Additionally, 13

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I believe my degree in mathematics has made me a better thinker and problem solver, which is always a helpful skill to have! Teaching at a boarding school is a lifestyle choice. Your job is much more than a 9-to-5 job. After your academic day, there are coaching and dorm responsibilities, student performances to attend, extra help to give, etc. However, for the right person, it can be an extremely rewarding job. You become part of a community and are able to see student growth far beyond the classroom. I would recommend that anyone interested in teaching at a boarding school do a summer internship at a residential school. It’s great experience and gives a good glimpse into the boarding school community. After teaching for 11 years, I wanted to explore other career opportunities in education. I always enjoyed creating lessons, projects, and assessments, and so I decided to see if I could make a career for myself in this realm. At the time, Khan Academy was hiring, and I was lucky enough to get contract work with them as a content developer. In this role, I created problems and solutions to help students learn math. I also wrote interactive math articles and reviewed the work of my colleagues. I loved this job and was very grateful for the experience, but ultimately, I missed interacting with students and being in the classroom.

Ebonii Bell

Senior Supply Chain Analyst Abbott (Formerly St. Jude Medical) Spelman College BS Mathematics and Computer Science Rice University MA Computational and Applied Mathematics

I started my career as a Systems Integration Business Analyst with a Fort Worth-based aeronautics company. I was assigned to support the development of a management level resource tool, and spent most of my time granting users access to the tool and auditing usage data, only occasionally conducting actual analyses. As a recent graduate with my bachelor’s degree and masters under my belt, I was quickly bored with the monotony of the role. Within a year, I transitioned into a position at the same company as a Systems Engineer. In this role, I got the opportunity to perform investigations using our team’s simulation modeling tool. I was primarily responsible for creating business case scenarios that allowed me to model the transport of parts and subsequently explore how delays in transport affected our success. After four years with that team, I got the opportunity of a lifetime working directly with the VP of Strategy. Though my job title was still “Systems Engineer,” I was actually continuing to grow as a business analyst conducting research on topics such as attrition trends in the industry and competitor strategies. With more than ten years of industry experience primarily as a Systems Engineer, I decided to transition to another company as a Supply Chain Quality Engineer responsible for leading on-site supplier engagements to drive top performance with subcontractors. This particular role required an extensive amount of travel. Being away so much put a strain on my young family, and I missed datadriven assignments. As a Supply Chain Quality Engineer, I developed a curiosity for understanding the effects of supplier relationships on the business, which led to my current role with St. Jude Medical. As a Senior Supply Chain Analyst at St. Jude Medical, I manage the tool we developed to assess risk within our supply chain. This tool uses purchasing 15

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data, performance information and other risk factors to assign each supplier a risk score. I often run reports on specific suppliers and provide explanations of the risk in starting or continuing a business relationship with the supplier. I also lead cross-functional review team meetings with each of our sites, and make appropriate recommendations for actions to reduce risk and/or identify cost savings opportunities. Our team consists of about six engineers and I am the only analyst. There are three of us here in Plano, Texas, with the rest of the team working at other sites across the country. The team in Plano collaborates on new ideas and developments for the risk assessment tool, but as the sole analyst I am responsible for the data scrutiny and tool support. I have always been inquisitive, and my degree in mathematics helped fine tune my abilities to dissect large amounts of data and make sense of it all. In each of my roles, I have had to investigate problems and find solutions. I am not intimidated by large amounts of data, and I welcome the challenge of uncovering the source of an issue. When we want to add new logic to the tool, I am able to use my mathematical and computer science skills to create algorithms that get us to the best solution. I must admit that it is difficult to manage a full time job, a spouse, and three young children. I am very involved in my boys’ education, so when I get home, I usually spend at least an hour or two going over their school work. They are all very active in sports and other extracurricular activities, so I try to be present for it all. I am fortunate to have a manager that supports my desire to be at every class party, spelling bee, and awards program, but it can still be stressful balancing it all. I would advise an individual interested in analytical work to find an industry they are truly passionate about. That may mean taking internships during the summers or shadowing professionals in that industry so that you discover if you like it or not. You will be successful if you are enthusiastic about what you do. If you find the work no longer makes you happy, don’t be afraid to seek another opportunity that excites you more.

Robert M. Bell

Statistician (retired) RAND, AT&T Labs, and Google, Inc. Harvey Mudd College BS Mathematics University of Chicago MS Mathematical Statistics Stanford University PhD Mathematical Statistics

My field, statistics, is the science of collecting, analyzing and interpreting data, and communicating uncertainty. In 35 years at three companies, I’ve been blessed to work with experts from many different scientific disciplines on problems in areas ranging from public policy to the internet. After getting my BS in math, I wanted to pursue a graduate degree in something less abstract. I was attracted to statistics, at least in part, by a childhood interest in baseball statistics. But learning about the breadth of problems where statistics is instrumental was what hooked me for life. My first statistics job was at the RAND Corporation, which performs public policy analysis. One of my most interesting projects was to evaluate the effectiveness of a substance abuse prevention curriculum for junior high school students. Besides analyzing the data that was collected, I played a critical role in designing the experiment: who should be in the experiment, which students would receive the curriculum and which would serve as “controls,” and what data should we collect? We needed to learn about the students’ use of substances—from cigarettes and alcohol to cocaine and heroin—which we could only learn from self reports. Validating those reports was critical. Amazingly, if students are convinced that their reports are confidential, the vast majority will report honestly. We demonstrated this, in part, by collecting saliva specimens in test tubes (yuck!) that were tested for evidence of tobacco use and compared with corresponding self reports. 17

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Over the second half of my career, I worked in the tech industry at AT&T Labs and later at Google, where statistics remains in high demand. For example, Google is continually making changes to its search and other products. No change goes into full-scale production without its effects being evaluated in a randomized experiment. While many experiments are simple to set up and analyze, others raise thorny challenges. How do we tell whether a page of search results successfully answered a user’s question? How do we assess the effects of a new interface that may change over time as users get used to it? How do we assess a change when some users leave our site before we can collect the main outcome of interest? All of these questions require using experience to integrate the “math” of a situation with real-life considerations. While at AT&T, I competed with two colleagues in the Netflix Prize (www. netflixprize.com), a worldwide data analysis competition that offered $1,000,000 to a team that could improve by 10 percent on Netflix’s own algorithm for recommending movies to its customers. We started working on the problem, not because we expected to place high, but in order to learn something about a type of data analysis that we knew little about. Well, after about eight months, we reached the top of the contest’s real-time leaderboard; and we were hooked. After 33 months, and mergers to add four new teammates, we won the Netflix Prize! No, we didn’t get to keep AT&T’s share of the million dollars, but we did convince the company to contribute the money to programs that support STEM education. And we achieved our original goal—to learn about an area of statistics that was new to us. The moral is to always look for new challenges.

Nicholas Bennett

Research Scientist Schlumberger University of the South BS Mathematics Yale University MA Mathematics PhD Mathematics

I work as a research scientist at Schlumberger, an oilfield services company that provides measurements of the Earth acquired while prospecting for oil and gas. I have been working more recently with acoustic measurements generated using a 5-10 kHz source mounted on the exterior of a steel tool sonde (a type of instrument probe) deployed in a borehole that has been drilled in the Earth’s subsurface. The sonic waves generated by this source propagate through the various nearby rock layers (sandstone, limestone, clay, salt...) that may or may not be filled with various fluids (water, oil, natural gas, carbon dioxide...). Depending on the acoustic impedance contrast between these layers, some of these sonic waves may be reflected and then subsequently recorded by receiver sensors which are also mounted on the exterior of the same steel tool sonde. Additionally, these sonic waves may reflect off faults and fractures, perhaps undergoing a mode conversion from compressional to shear or vice versa. These recorded wavefields can be used to image or map these nearby formation structures, and such maps/images typically have much higher resolution than what can be obtained via surface seismic or similar measurements that employ a much lower source frequency. However, obtaining an accurate image of these features requires a correct interpretation of these reflected sonic wavefields. Discerning the propagation speed and ray path of these reflected waves is critical. Meeting this interpretation challenge involves recognizing some of the physics of the receiver arrays used to record these wavefields and developing the mathematics processing that can make the best use of this physics understanding. In 19

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this case, it is important to consider that our receiver sensors are deployed as a 3D cylindrical array spaced linearly along the length of the tool sonde and around the circumference of the sonde. When a plane wave arrives at this 3D array, the arrival times vary linearly as a function of the spacing between the receiver sensors along the length of the tool and sinusoidally as a function of receiver position around the circumference of the sonde. We can observe this phenomenon in measurements collected in the field and through detailed computer modeling. The story of developing the mathematics processing that uses these observations is beyond our scope here, but an important aspect of this work has been quantifying the precision with which we can determine the propagation speed and direction of these wavefields. My experience of working in industry has shown me that collaborating effectively with other people whose core expertise is not necessarily mathematics is an important skill to improve whenever possible, but especially while one is in school. I would recommend seeking out internships and summer jobs that provide opportunities to see how math is used every day. I spent two summers while in college working in the Director’s Summer Program at the National Security Agency at Ft. Meade, Maryland, where a lot of interesting math is needed to effectively and efficiently process signals to find useful information. I also spent two summers working as an intern at Schlumberger while in graduate school, and this provided an excellent introduction to what a mathematical career in industry might be like. If you are an undergraduate student who might be interested in graduate school, I would recommend looking into the many Research Experience for Undergraduate programs held at various universities. I participated in one held during the summer at the University of Tennessee and learned how interesting working on mathematics that is not already printed in books can be. Lastly, if you are an undergraduate student who might be interested in studying abroad, I would recommend the Budapest Semesters in Mathematics program. Their signature problem solving course “Conjecture and Proof” and their courses on combinatorics showed me some of the rich diversity of cultures within the mathematics community. This awareness has served me well.

Nicole Bertram

Software Developer Epic Systems Corporation Bemidji State University BS Mathematics and Biology, Chemistry Minor University of Wisconsin–Madison MS Cellular and Molecular Biology

I ended up taking a little bit of a scenic route to my current job. I began my college education thinking I wanted to work in healthcare, as a Physician’s Assistant. Mathematics was always part of the plan, since the skills learned while working on a math degree are applicable to a wide variety of careers. Soon into college I turned my focus towards research: as an undergraduate I worked on two research projects which used mathematics and computer science to solve biological questions. One of these projects involved using both bioinformatics techniques and biochemical techniques to investigate the three-dimensional structure of RNA molecules. Having degrees in both biology and mathematics made me uniquely suited for working on projects such as this. As a graduate student in cell and molecular biology, my mathematics background allowed me to plunge right into the new and exciting area of big data, using large scale data-sets to answer biological questions. I worked on a project that involved the analysis of whole-transcriptome (the set of all RNA molecules) data to study how an organism’s gene expression can be affected by environmental stressors. My statistics background was useful almost every day while working on this project. Statistical programs such as R were necessary to be able to analyze these large data sets. This knowledge in statistics also helped me design my own experiments, since I understood the importance of replicating a single experiment many times in order to have results you could be confident in. And of course, it helped me to analyze those results using the correct statistical methods. 21

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Today, I’ve come almost full circle from where I was at the beginning of college: working in healthcare, but on the software side of the equation. I work as a software developer designing and developing the software that doctors, nurses, pharmacists, and other hospital employees use to document information on your medical chart. It’s a job that offers very meaningful work, since the features I develop contribute to helping clinicians provide the best possible care for their patients. Skills I obtained from my math degree, such as an ability to think about complex problems and break them into their smaller components in order to efficiently solve the problem, are quite helpful in a job like this. Intellectually, there is quite a bit of variety in my day-to-day work. I love developing software to solve interesting and challenging problems—and health care has no shortage of interesting and meaningful areas. One of the most interesting aspects of my software development career is the fact that our company encourages developers to see a project through from start to finish. We are involved in our software projects right from the start, helping to define the specific features we should add to the software in order to make patient care better. Some days, I’ll be talking directly to the people who use our software every day, asking them what they need from the software and getting feedback on development that I’ve done to create new features for them to use. Of course, a large portion of my job is still dedicated to actually writing and testing computer code, but I find the ability to speak directly with the clinicians that will end up using the software I’m working on helps establish meaning behind the work that I do. If I were to offer advice to those starting out in their career in mathematics, I would encourage them to be open to a variety of disciplines (such as biology!) and areas, because a degree in mathematics can be used to help solve any sort of problem you could possibly think of. Also, during my college career, I found research experiences for undergraduate (REU) opportunities to be invaluable. They allowed me to apply the knowledge and skills that I was learning to questions that no one has yet solved, which you don’t often get a chance to do in a classroom but are always asked to do in your career.

Toni Bluher

Subject Matter Expert in Cryptography National Security Agency Mathematics Research Group Indiana University BS Mathematics Cambridge University Certificate of Advanced Studies Princeton University PhD Mathematics

I started on an academic career path earning a PhD in mathematics. Originally, I planned to be a professor, but the job market in academia was unfavorable in 1994 when I was looking for a permanent position. I met some people from NSA at a conference and thought it sounded like an intriguing opportunity because of the plethora of interesting projects. After the conference, I decided to apply to NSA. Skill in mathematics is highly valued by the NSA, so they were happy to hire me. I have truly thrived here, enjoying the varied and fascinating mathematical projects in support of national security from the moment of my arrival in 1995 to the present. From my perspective, being hired at NSA was the best thing that could have happened to me. I use advanced mathematics every day in my work. The projects we work on are challenging and open-ended, and our success depends entirely on our skill in mathematics and our ability to apply that skill in new and creative ways. The job is very fulfilling. I have studied many questions that are related to “one-way functions,” which form the mathematical basis for public key cryptography. For example, how secure are they? What are new applications of one-way functions? How would a quantum 23

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computer affect them? I have also worked on code breaking, and on making algorithms more efficient. Many people in my office are experts in statistics and work on data science. Others work on designing the next generation of secure communications. There are many projects to work on, and one of the biggest challenges is to prioritize which will have the most impact. Overall, my job feels like an academic job – I do research, write papers, attend seminars, give talks, collaborate, and mentor. The main differences are that I don’t apply for grants, I don’t teach, and, since most of my work is classified, I can’t talk about what I am working on once I leave the building. Also, the work at NSA is more collaborative than in academia; for example, I just finished a year-long project involving a team of ten people. I currently have two new interns from Math Development Programs who are just starting a six-month tour. (The Math Development Programs are 3-year programs for new hires during which they take courses in cryptography and related subjects and also do several six-month tours with a mentor.) They are learning (very quickly) the background that they need in order to work on our project. We have an open office environment, but because I sit in a corner, my area is quiet. We have a coffee/kitchen area and a daily tea at 3pm. The atmosphere is friendly, and a lot of collaboration happens. I take full advantage of flexible hours and an informal dress code. (Blue jeans and comfortable shoes for me!) During summers, I have often gone to SCAMPs, which are focused research opportunities coordinated by the Institute for Defense Analysis, or I have mentored undergraduate math students in the Director’s Summer Program, which is a summer REU during which students receive a TOP SECRET clearance and work on mission problems. Work/life balance is a major plus for working here. My work week is forty hours, and I am not pressured to work extra hours. When I started my job 23 years ago, I had a 3-year-old, a 5-year-old, a 7-year-old, and a mother who lived in Indiana and was just diagnosed with cancer. The flexible hours made it possible to drive to Indiana when my mother needed chemotherapy. Now my life is much easier, and I use the flexible hours to get exercise during daylight hours. Also, I have two grandchildren who live nearby, and on nice days, I sometimes leave early to take them to the park. If you have a passion for mathematics and problem-solving then you would probably enjoy working in cryptology. I recommend taking courses in advanced algebra, computer science, probability, statistics, and any other math classes that seem interesting to you. Also, participation in Research Experiences for Undergraduates and other internships is extremely valuable, including some that are offered by the NSA. (See the website www.nsa.gov.) There is no single “model” for who can be successful, but general qualities of creative approaches to problem-solving and a willingness to dive into problems and learn new things are essential. A bachelor’s degree is required.

Kate Brady

Senior Bicycle Planner City of Colorado Springs Carleton College BA Mathematics School of Architecture University of Virginia MA Urban and Environmental Planning

I am a bicycle planner for the City of Colorado Springs, Colorado. I work within the Public Works Department, but work closely with Parks and Rec, Communications, Economic Development, Planning, bicycling advocates, and others. The goal of my program is to get more people riding bicycles for transportation and other reasons. Some of my current projects include: overseeing consultants who are creating a Bicycle Master Plan for the city; filling out an application to the Bicycle Friendly Communities program; establishing priorities for the bicycle budget; retrofitting bicycle lanes on existing roadways; explaining bicycle lane projects to the public; evaluating projects based on data collected; figuring out how to reorganize an advisory committee to work more effectively; and monitoring crash reports for any involving people on bicycles. I’ve had a long and varied career path, through several fields and different regions of the country. I gradually discovered what I wanted to do, which was to work with people to make the world a better place. I attended grad school in urban planning, and then a few years later took an opportunity to pivot from more general comprehensive planning work to bicycle planning. I’ve ridden bicycles since I was eight years old, and commuted by bicycle to almost every job I’ve had, so I was able to apply both education and life experience to a growing field. I am a program of one, with a very ambitious stated goal, so my days often include meetings with other people from other departments or organizations, to coordinate our work (or persuade them to help the cause). I am lucky that I work 25

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with a lot of other people who find bicycle planning interesting, and who are very willing to contribute their expertise to my program. I usually have some time working alone in my office, answering emails, writing documents, etc. Occasionally I will have evening meetings, because we need to work with the public on projects, soliciting suggestions, and letting them know what is happening, and they are most likely available after the work day. My best days include riding my bicycle to a meeting or site visit. I first worked in software development right out of undergrad. That job gave me a solid technical skill set and some savings that allowed me to take some risks later in my career trajectory. In my experience, my math degree has opened doors in less traditional fields for a math major, because hiring managers assume I am smart, and that has gotten me interviews. (It was my job to ace the interview, of course.) Because my work involves spending public money to change how people move around the city, there is a strong emphasis on data-driven planning citywide and data-driven evaluation at the project level. At the very least my mathematics background means that I am not afraid of data (which a surprising number of people are), and at the best, it allows me to find creative ways to conduct analyses when the data that is available to us is not quite what we need. When I have worked in very small organizations, I did a lot of that analysis myself, which was helpful. Now I work for a larger organization, but I am able to work closely with the City’s full time analysts. My bike lane projects are typically paid for with public monies, and we have an obligation to make sure that the money is well-invested. The City needs to know whether any given project is successful (e.g., people are riding their bicycles more because of the new bike lane), and show it through data analysis. My city has a few (expensive) automatic bicycle counters that we can use to get 24-hour or longer counts of bicycle usage, but we also have a number of (inexpensive) volunteers who are willing to sit by the side of the road and count bicycles for two hours. How can we use automatic (and presumably more reliable) data collections to find meaning from very short duration volunteer counts? How many 2-hour counts do we need to consider the data reliable? My job in Public Works is at the intersection of planning and engineering. There are lots of opportunities for engineers who like bikes, though that wouldn’t be my job specifically. GIS (a collection of systems for managing and analyzing geographic data) would be another entry point of interest to math majors. I choose to believe that a wide range of activities and interests make me good at my job. Math can get you a long way, but at heart I work with behavior change, and people’s response to change, both of which are messy and uncomfortable, far from the logic that I liked so much about math.

Marina Brockway

Chief Technology Officer and Founder VivaQuant Kiev State University, Ukraine MS Mathematics PhD Mathematics University of Minnesota MBA MS Physiology

I was always interested in solving puzzles, but I wanted to apply my interest to real-life problems, so I got a degree in applied mathematics. When I arrived in the USA, my experience was mainly in control theory as applied to spacecraft design problems. However, I was more intrigued by the possibility of applying my knowledge to physiology and medicine and was looking for a way to transition into that field. I got just the right opportunity through a postdoctoral fellowship at the Institute for Mathematics and its Applications (IMA) at the University of Minnesota. The IMA featured a year of workshops focused on the applications of mathematics to emerging problems in medicine. The institute’s location in Minnesota, a hot bed of medical device companies, was ideal for bringing together speakers from industry and academia. When I joined Guidant (now Boston Scientific), I gained even deeper insight into where and how mathematics could be applied to medical devices to improve performance and help more patients. When I entered the medical device industry, computing power was rapidly increasing, new sensor technology was advancing, and the power consumption and size of computing chips were decreasing. It was apparent that these advances would open up opportunities for more sophisticated algorithms that could improve healthcare. In addition, there were many advances in physiology and understanding of disease mechanisms. These advances provided a foundation for how to address significant problems in medicine, such as how to predict when a patient might be at risk for hospitalization due to deteriorating heart health. To gain better understanding of these health problems, I learned physiology and found that it was most helpful to view problems in the field through the lens 27

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of a mathematician. Nature often comes up with the most efficient and practical solution. Mathematicians have a toolset to understand, quantify and emulate this approach, all the while being aware of the assumptions we make to simplify the problem at hand. Learning to dissect a complex problem into feasible steps and methodically solve them is another great foundation of mathematical education. The explosion of wearable devices that are used in fitness and healthcare is bringing new challenges and opportunities for the medical device industry. Much more useful information can be collected on the patient’s health state, but the signals are often contaminated with noise as the devices are worn in everyday, active life. The number of alarms that health monitors currently generate is staggering and the volume of data is overwhelming. Eliminating noise in signals collected by wearable devices could potentially help enable their success. With this in mind, I founded VivaQuant, a firm focused on devices and software that improve the accuracy of information extracted from data obtained from ambulatory patients. With support from the National Institutes of Health, VivaQuant has developed an embedded and PC-based software that removes nearly all noise from electrocardiograms obtained from wearable devices as patients go about their normal everyday activities. We’ve also licensed our technology to a multinational sports apparel firm for monitoring athletes. This technology is not only very effective at removing noise, it also is extremely power efficient, rendering it suitable for use in implantable and wearable devices. The technology is being used for evaluating the cardiac safety of new life-saving drugs and devices and is currently pending FDA clearance for long-term monitoring of cardiac patients. Working for a medical device start-up is like running a marathon: it is strenuous and rewarding at the same time. I recharge when spending time with my family pursuing hobbies that are mutuality inspiring: board games, art, gardening, and sports that we enjoy: tennis, skiing, and cycling.

Sarah Brown

Senior Scientist NATO Communications & Information Agency Oberlin College BA Mathematics and Computer Science University of Maryland, College Park MA Mathematics

My degree in mathematics led me to fellowships with Sandia National Labs and the National Academies during graduate school, and these experiences inspired me to look for opportunities to work on problems rooted in mathematics and computer science whose solutions serve the national public interest. I spent three years settling comfortably into my first real job after graduate school, working at The MITRE Corporation in Washington, D.C., where I performed security audits, market studies, and security architecture analyses for various government organizations. It was exciting work on a strong team, but I soon found myself planning a wedding with my long-distance fianc´e, who had many exciting job offers of his own, none of which were in D.C. Not wanting to compromise on either of our career opportunities, we explored a lot of options until we found an exciting solution. He could complete a 2-year postdoc in Amsterdam at the Vrije Universiteit and I could work on a new set of cyber security challenges for MITRE, on site at NATO, in The Hague. It did not take long for us to fall in love with all of the experiences The Netherlands gave us, and we are still calling this country home. As a US liaison at NATO, I became interested in cyber security information sharing standards and frameworks for describing cyber threats. As cyber threats and attacks become more and more sophisticated and widespread, being able to collaborate is an important requirement for NATO and organizations worldwide. Now I work in the field of cyber security where I focus on strengthening the cyber 29

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security posture of member nations and NATO infrastructure. One of the most enjoyable topics I’ve worked on to date is the challenge of bringing cyber security threat analysts and systems together for more efficient collaboration against cyber threats. My days often involve discussions with the other members of the team, ranging from technical to budgeting and resources. I engage with external customers and stakeholders as well as other internal teams—from IT infrastructure to marketing— as needed. Through mailing lists and face-to-face meetings I stay connected with external industry experts to bring current research to bear on my projects. In general, a mathematical background is very valuable for breaking down problems into distinct parts and thinking logically to design solutions. Specific types of projects I’ve worked on and their related mathematical disciplines include: designing solutions that balance complex sets of requirements (linear algebra, optimization), creating and using well-defined, repeatable processes (logic, discrete math), designing comprehensive frameworks to capture a topic (logic, structures), the use of standards in system design (relations between objects, graph theory), or analysis of cryptographic and key management protocols (cryptography, algorithms). I took on a new opportunity in 2013 and joined a dynamic Dutch cyber security startup, Fox-IT, where I worked on a team tracking cyber threats and attacks targeting banks around the world. There, I led an effort to restructure the data collected according to international standards, thereby allowing information sharing at the machine-to-machine level, not just human-to-human level. As a result, millions of pieces of data were shared, investigated, and managed per day, resulting in direct savings for banks that can defend their networks better and faster against the latest threats. I’ve recently rejoined NATO, now as an official staff member, and am looking forward to new and exciting challenges in cyber defense information sharing, as well as many other areas in the future. Living in The Netherlands has been a wonderful influence on my work and family balance. With many leading cyber security organizations based here, it is an exciting place to work with many opportunities to grow professionally. In addition, the European lifestyle places a very high value on family time, with average annual leave at 30 days, around 15 national holidays per year, and flexibility in work arrangements to allow workers to manage important aspects of their life. As a result, my husband and I are able to spend time with our children as they grow and be part of an active community of families and friends where we live, while having substantive careers. Fortunately, cyber security is an ever-expanding field growing with so many focus areas. My advice is to be on the lookout for opportunities to contribute to solutions that make a difference in the world, collaborate with people from different backgrounds, and be open to new opportunities. You never know what is waiting out there. Once you discover what you want, don’t be afraid or get discouraged, keep going for it!

Lisa Byrne

Data Scientist WeddingWire St. Mary’s College of Maryland BA Mathematics Georgetown University MS Mathematics and Statistics

My undergraduate math professors always said that a degree in mathematics teaches you how to think, and I found that to be my most marketable skill when I graduated. My first job was as a Business Strategy Analyst at a large insurance company. I knew nothing about business, strategy or insurance, but I knew how to think critically, ask questions, and take creative approaches to solving problems. I learned more technical skills on the job such as querying databases with SQL, building financial models in Excel, and using logistic regressions in SAS to predict customer churn. As I continued to work with data to try to understand and predict customer behavior, I realized that I could benefit from more extensive training in statistics. I decided to pursue my Master’s degree part-time while working full-time. In my classes I learned more about probability theory, mathematical statistics, regression and data mining. I also became proficient in the statistical programming language R, which I now use extensively in my current job. I now work for an internet start-up that houses millions of business reviews and serves as a platform for consumers to find and connect with small businesses with limited online exposure. My team works with all departments in the company: sales, customer service, marketing, finance, and product development. We identify and analyze the data they need to make strategic decisions and we set up reporting to help them monitor key metrics that are essential to their success. I spend 31

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most of my day pulling and cleaning data, building charts, communicating results, collaborating with teammates, and meeting with internal clients. The best way to describe my work is through some of my most recent projects. Recently I helped the email marketing team design, implement, and analyze a test of two emails to see which one was more successful in leading consumers to take action. I worked with the sales team to understand how long each step of the sales process actually takes. The product team rolled out a new feature on the website and asked me to measure its impact on web traffic. An executive asked for a prediction of when our company would reach a certain milestone. I use my math degree every day. All of my projects require the logical and analytical thinking that I developed in my study of math. Some projects require more explicit use of mathematics such as experimental design, hypothesis testing, or building predictive models. New analytical techniques and software packages are developed constantly, and I can’t possibly know all of them. What’s important is that I can find them and implement them when I need them, and that’s what my mathematics background has equipped me to do. If you want to pursue a career in business analytics and data science, there are now Master’s programs that have been designed with this specific focus. However, a graduate degree isn’t necessary to get started. There are a lot of free online courses that can teach you the required technical skills (SQL, R/Python) and the basic concepts behind predictive modeling. Undergraduate electives in computer science, applied mathematics, and statistics and probability theory would also help prepare you for this career path.

Jenna P. Carpenter

Founding Dean Professor, School of Engineering Campbell University Louisiana Tech University BS Mathematics Louisiana State University MS Mathematics PhD Mathematics

I am building an engineering school from scratch! I started a couple years ago with two computers, three offices, and a handful of ideas. I have hired a team of faculty and staff, and together we have built the curriculum, designed teaching and learning space and labs, created marketing materials, initiated outreach activities, and attracted our inaugural class of 90 freshmen (our goal was 50!). My combination of administrative experience, teaching experience, nationallevel involvement in engineering education through several professional organizations and national initiatives, national network of collaborators, passion for attracting students to engineering, and desire to build an innovative engineering program that attracts a diverse group of students got me the job. We are new and small, so no two days are alike. My job may be a lot of things, but boring isn’t one of them! I am constantly learning, expanding my own skills and experiences. A typical day is a mixture of meetings with both on-campus colleagues and off-site at various corporate and non-profit partners, visits from prospective students and their families, teaching, problem-solving (when you are building a new engineering school, there is no shortage of problems to be solved!). As a new program, we have a lot of freedom to develop innovative solutions. I brainstorm with our faculty and staff to develop courses, extra-curricular activities for students, new teaching and learning space, along with a healthy dose of travel 33

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to speak to groups across the nation about creating a culture that supports the success of women in engineering. There are times where I have to sit at my desk (or in my favorite chair at home) and write, create, develop for several hours at a time. Other times, I am out and about on campus, in the region, or very often running through the Atlanta airport on my way to speak somewhere, all of which requires me to work with a team of colleagues. Being able to communicate clearly, work with a team, and come up with innovative solutions to problems are all key skills. A mathematics degree teaches you to communicate clearly, logically analyze a problem, and develop multiple solution strategies, create totally new approaches to a problem and more. My advanced degrees are in pure math, so all of that theorem proving develops these skills (even if you don’t realize it at the time). The broad technical background I received has enabled me to understand a wide spectrum of applications of math and science, as well as the enormous changes in technology that have flooded the world during the course of my career. Simply put, I know enough to understand the basics of a lot of things and I know how to learn whatever it is that I don’t know or understand. With that, you are equipped to do almost anything you want. To be honest, I don’t solve any math problems outside of the classes I teach. But my understanding of how math is foundational to an engineering curriculum, the types of skills and habits that students need to develop in math class which enable them to be successful in later engineering courses, the ways that math concepts are applied in engineering, what type of math preparation students need in high school to be successful engineering students in college, and how technology can both impede and facilitate student learning in mathematics and engineering are all central to my daily work. I use this knowledge every day. I actually don’t like the phrase “work and family balance.” The word “balance” implies that everything has to be even in some fashion, that you have to spend equal time on everything. Instead, I use the term “worklife fit.” What does that mean? Let’s say that you and I wear the same size blue jeans. The odds of a pair of jeans fitting us both is slim. I am short, you may be tall. I have a long waist, you may not. And if we can’t both wear the same pair of size 10 jeans, odds are that neither of us would really be upset about that. So why do we feel like we all have to fit work and family into our lives in the same way? It’s very personal – there is no one right way. Do whatever fits you and your family at the time. I have had to juggle work and family in a number of different ways over my career – sick and aging parents, job changes, career advancement – all have forced me to adapt. Do whatever works for you and your family at this time. And don’t worry about what anyone else does or thinks. If they don’t sit at your dinner table, it’s none of their business. Don’t turn down an opportunity to learn something new, even if you can’t see today how you will benefit from it; people take all kinds of circuitous paths to reach their goals. If you have to do something that you don’t want to do, figure out how to turn it into a plus for your career. As a department head, I had to lead our reaccreditation efforts, which required hours and hours and hours of my time. I decided that I needed to capitalize on all this expertise that I was gaining, so I became an accreditation evaluator. My accreditation evaluator experience was one of the key reasons I was hired as a founding dean.

Tim Chartier

Professor Mathematics and Computer Science Davidson College Western Michigan University BS Applied Mathematics MS Computational Mathematics University of Colorado Boulder PhD Applied Mathematics

I’m a professor of mathematics and computer science and a big part of my job is playing sports – not on the field, court, or track, but on a computer or with paper, pencil, and a big eraser. I’m one member of a team that keeps growing. This year, I’m working with nearly sixty undergraduate students at Davidson College. Last year, the group was nearly thirty, and the year before, we were thirteen. This all began with three students walking into my office four and a half years ago. The request was simple: can we form a group to supply statistics and analytics to the Davidson College men’s basketball team? My research already overlapped with sports, as I had helped develop mathematical algorithms that create brackets for March Madness. This would be different. At the time, my existing research fell entirely in the field of numerical linear algebra. In this project, we’d tackle whatever questions the coaches posed. Those three students were engaged, hopeful, and fully committed to the project. So, we agreed to move forward and contacted the basketball coaches. Soon, we were in weekly meetings making progress toward offering analytics. The work only occasionally involved linear algebra, but it always encompassed a main passion of my work as a professor: engaging students. Fast forward to now; the group that began as three is now approximately sixty in our fifth year. We supply analytics for men’s basketball, women’s basketball, women’s soccer, and football. Our success led to projects with professional teams 35

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in the NBA, NFL, and NASCAR. We’ve fielded analytics questions from The New York Times, ESPN, and the Washington Post. How do we manage the projects? First, students take leadership in their work. While we carefully talk through approaches and techniques, a student is in charge of an assigned job and is expected to meet deadlines. The coaching staff depends on our mathematical insight, so we focus on accuracy and reliability. To keep things manageable, students direct different components, or verticals, of our group. Each subgroup works as a team and anyone can come and work with me as needed. At the same time, the leader of each vertical is the main contact with the most knowledge of the details pertaining to that vertical’s projects. My job involves a lot of meetings to discuss hurdles in student work. I also receive and send many emails to gauge and, quite frankly, motivate progress. I have both “to do” and “must do” lists. Even with sixty students, our ability to field questions varies. Media requests come without notice and often have short timelines. The key is for everyone to be clear and honest about their interest and availability. The same is true for me. Sometimes, I can help a lot and other times, I can only help with initial direction and final revision. Our clear communication enables us to make good decisions and work on projects successfully. For me, there is a huge pay off for the busy-ness. I joined the faculty of a small liberal arts college in order to be active in students’ learning. I get to do this with sports analytics. Further, I share in experiences where students have commonly looked at me and stated, “I will remember this moment for the rest of my life.” To me, my sports analytics group is a large classroom where we learn together and push forward on our projects, ready for unexpected requests to come our way and engage us as we travel directions we’ve yet to discover.

Bill Correll, Jr.

Research Scientist Radiant Solutions Denison University BS Mathematics University of Michigan MS Mathematics PhD Mathematics

I have been working as a remote sensing research scientist for seventeen years. Towards the end of graduate school, I had concluded that I did not want to try to make a go of a lengthy career in Algebraic Combinatorics, even though I enjoyed teaching math classes. My friend and older classmate Pat Bidigare, now a technology director at Raytheon BBN Technologies, shared my academic background and my doctoral advisor. From recruiting to serving as technical lead on some of the first contracts I supported, Pat was instrumental in bringing me into the field. My first day on the job was September 10, 2001 – a significant moment to be embarking on a career in remote sensing. I remember feeling awkward about sharing esoteric findings of my doctoral work in my job interview. However, employers are forever hungry for people with quantitative and computational skills. I have been learning about signal and image processing and radar systems on the job from colleagues and textbooks ever since. Flextime eased the transition from less structured days in graduate school. My office is solitary and quiet, allowing for deep concentration for problem solving. Our office community is collaborative and social. There are many great traditions like a chili cook-off, golf league, sand volleyball league, and disc golf outings. After several years, my job started to become more entrepreneurial with involvement in proposal writing and business development activities. If you use math in industry, plan on being comfortable with algorithms and computations and not dealing regularly with theorems. My degree in math helps me to understand as well as to create and improve signal and image processing algorithms. Knowledge of geometry, signal processing, filtering, and hypothesis 37

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testing are all very helpful for me, and this knowledge relies on a background in mathematics. For example, a fundamental step in Synthetic Aperture Radar image formation involves the fast Fourier transform, a powerful signal processing algorithm which combines ideas from linear algebra, number theory and complex analysis. In my work I am expected to formulate and solve a wide variety of problems and my mathematical background helps make this possible. My math degree has also been invaluable in my theoretical work on Costas arrays (classes of permutations with applications in radar and sonar target detection) and MIMO radar. It is a personal priority – but not a job requirement – for me to publish, and I enjoy pursuing research projects with connections to remote sensing. In 2016 my friends Chris Swanson and Randy Ho and I published an improved bound for the density of Costas arrays among permutations in an enumerative paper for Electronic Journal of Combinatorics. In 2017, I published another paper with Randy featuring the tightest known bounds on the number of 3-free permutations of the first n positive integers. It is vital to become known outside your building within your community of expertise. I recommend joining your professional society and utilizing its resources. I met many local engineers and scientists while serving my local IEEE Chapter (IEEE is a professional association for electrical engineering and related disciplines). I have attended the IEEE Radar Conference every year for many years. Participating in the conference, giving talks, volunteering time to referee papers, and serving on organizing committees have led to new research collaborations and opportunities. Signal and image processing are used in many technical disciplines and are very mathematical. Learning how to program (MATLAB, C++, and Python in particular) and having coursework in these areas as well as machine learning would be a good idea for anyone considering a career in remote sensing. I find that independent study works best outside of the office. I have been a long-time regular at a downtown Ann Arbor caf´e. This has been a great way for me to learn new things and meet new people.

Carla Cotwright-Williams

Computer Scientist Hardy-Apfel IT Fellow US Social Security Administration California State University, Long Beach BS Mathematics Southern University and A&M College MS Mathematics University of Mississippi MS Mathematics PhD Mathematics Old Dominion University Graduate Certificate in Public Policy

After barely graduating from undergrad and not having interest in teaching high school, I was motivated to apply for a science and math education PhD program. During my program, I completely turned around my academics and was doing extremely well. When I completed a master’s degree in mathematics, my thesis advisor suggested I consider a PhD in pure math instead of education. After finishing my PhD in math, I took a teaching postdoc, then accepted a tenure-track teaching position, although I was not sure if I wanted to teach or do something else. I allowed myself to follow my interests: taking a graduate-level policy course at a local university, being a faculty researcher with NASA and US Navy, volunteering in political campaigns, and earning a graduate certificate in Public Policy. With this background, I was awarded an American Mathematical Society Congressional Fellowship. During this awesome life-changing experience working on Capitol Hill, I decided not to return to my tenure-track position. After the fellowship, I spent the next year as a government contractor in the role of technical lead on a data analytics project at the US Citizenship and Immigration Services (USCIS). We looked at data quality within the legal permanent resident application process. When this project ended early, I looked for a line of work where I could continue to pursue my goal of using my mathematics and analytical thinking in a new way. Branching out from traditional job search routes, I learned about my current fellowship at a STEM Expo in Washington D.C. At this event, I was able to talk to 39

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a former fellow who now works at the US Social Security Administration (SSA). He shared his experiences. I was intrigued and wanted to know more, so I started doing research on the agency. Reading news articles and white papers I found online, I looked into the types of issues they faced. I looked at the future of data in the public sector. I knew with my personality, experience, and skill set, I could be a great fit for the program. I currently work for the SSA as a Hardy-Apfel Information Technology Fellow. As a fellow, I endeavor to learn as much as I can about data-analytics-related activities during four six-month rotations. During my rotations, while my primary goal is to become knowledgeable about activities to accelerate data-driven decision making (an agency critical priority), I am often afforded the opportunity to contribute to a number of projects given my advanced degree in mathematics and prior work in federal policy making. As a fellow, one of my primary duties is to learn about SSA. So many details and so much effort go into managing the digital records of the public: 165 million workers contribute to the Social Security program and more than 65 million people currently depend on monthly Social Security benefits. I often will set up meetings with leadership and subject matter experts to learn first-hand about the latest in benefits processing or technology which supports the process. When I have a particular project I am working on, I will conduct research (reading, web searches, or subject matter expert meetings) to get up to speed. My academic experiences help a lot in these instances. I often attend meetings where I provide subject matter expertise as one of a few PhD mathematicians in the agency; most of the time it is not related to math. I find that I can provide a purely analytical/logical or quantitative reasoning perspective, based only on the facts of the problem. In other instances, I am able to take facts and abstract them, or, vice versa, take an abstract idea and make it more concrete. The ability to take systematic steps through a problem, identify key parts, consider appropriate solutions, and test/validate the solutions is a very valuable skill, yet something mathematicians take for granted. The ability to think abstractly and apply general concepts to specific problems is also a greatly desired skill. In my first two rotations, the amount of mathematics I used in my work has varied. In a recent project, I needed to break down tens of millions of dollars allocated to particular IT projects into units of personnel resources: a linear equation with many variables and very big coefficients. However, there are efforts at many federal agencies to increase the use of data to improve and advance the business functions to provide better service to the public. I have always been involved with helping others. In my local community, I would tutor or volunteer with food donation drives. While in graduate school, I was Vice President of the Graduate Student Council. If you have the natural inclination to want to help others or find yourself able to learn and talk about anything under the sun with individuals academically or culturally different than yourself, you may possess the leadership and people skills essential to delving into the world of data science and policy.

Mimi Cukier

Mathematics Teacher The Park School of Baltimore Carleton College BA Mathematics and Philosophy

I teach high school math at the Park School of Baltimore, a K-12 progressive school. I first became interested in teaching while doing an internship at CITYterm, a semester-away program emphasizing experiential education. The teachers there were thoughtful mentors who helped me to prioritize long-term learning and reflection over daily concerns like grades and specific content goals. When I returned to teaching a few years later I recognized Park as a place in the same spirit. My colleagues and I aim to teach students to make sense of mathematics and to do mathematics themselves. Studying math in college helped me to see the depth, beauty, and structure present in high school algebra and geometry that I hadn’t seen the first time I learned those things. It also helped me to learn and practice the problem-solving strategies I explicitly teach my students now: make up a specific example, work backwards, look for patterns. After solving a problem, what further questions are there to investigate? My mathematics background also means that I can handle students’ questions without having to say “because that’s the rule.” When I’m leading a class, I think with my math brain, my social brain, and my logistical brain all at once. I come prepared with a plan for what we’ll cover and how the class will be structured. However, students’ questions, partially formed ideas, and even incorrect answers can lead down paths I wasn’t expecting. It’s my job to keep class feeling dynamic, and in the end to find a way to cover the required material by connecting the threads of our conversation. I love the fact that there is nothing repetitive about my job. A typical day requires that I read, write, do math, teach math, and talk to teachers, students, 41

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administrators, and perhaps parents. I check in with other teachers to seek out and offer advice. After seeing how class goes, I often write or find problems for my students that I think will be good follow-ups for the next session. I work with students one-on-one, talk to advisors and teachers about students we have in common, and go to meetings in which we discuss larger issues related to the school. If you think you would like to go into teaching, seek out the people or programs you respect enough to help shape your worldview. Be skeptical of any program that doesn’t get you into the classroom pretty quickly: educational theories set the groundwork, but kids will give you the most direct feedback about what engages them and makes them feel valued. While you’re in college, see if you like teaching by tutoring in your peer help center or doing outreach programs with local kids. At the same time, college is a time to try new things and find out what you are passionate about. When working with students, you bring your whole personality, including everything you love, to the table. The more topics that excite you, the more experiences you’ve had, the better you’ll be able to find common ground.

Michael Dairyko

Senior Manager – Data Scientist Milwaukee Brewers Pomona College BA Mathematics Iowa State University PhD Applied Mathematics

I am a Data Scientist for the Milwaukee Brewers Baseball Club. To friends and family, I describe my job as being similar to the movie “Moneyball,” but for the business side of the organization. In a nutshell, I use machine learning to provide forecasted insights centering around ticket sales and revenue. While I do not necessarily use the mathematics related to my dissertation or any high-level proof techniques, this process involves creativity and problem solving, which is the core of any mathematician’s training. I equate the level of difficulty as being similar to conducting the research for my dissertation. There will be lots of failed attempts at solving for the answer, but being persistent is vital for success. My path to becoming a data scientist has been an interesting road. I first discovered my love for mathematics while taking a Linear Algebra course at Pomona College. This experience prompted me to spend my summers participating in various Research Experience for Undergraduate programs, where I was exposed to high-level mathematics research. As my undergraduate experience came to a close, I decided to pursue a doctoral degree at Iowa State University. At that time, my career goal was to become a professor at a liberal arts college. However, I decided to alter that goal after I took a course in machine learning. 43

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Throughout my undergraduate and graduate experiences, I had a number of opportunities to network with professionals in mathematics and related fields. Because of that networking, I was contacted to interview with the Brewers organization. One of my mentors recommended me as a mathematics PhD with an interest in data science, and it was a great fit. A normal day with the Brewers begins with a stand-up meeting with IT department collaborators to catch up with the progress on projects, brainstorm ideas, and give assistance with any problems that arise. The majority of my time is spent making queries in SQL (a database language) grabbing particular views of data contained in our database, coding in Python to process data and build models, and sitting in meetings with staff from other departments to discuss and align the forecasted results. I also handle administrative tasks involving exposing the results to the organization and providing insights for various statistical or forecasting questions that arise. Prior to my arrival, my department was remodeled to foster collaborative work. The results have been amazing and, in my opinion, there is a healthy mix of collaborative and solitary work. Data science is a huge buzz word in the world these days and has various applications. Overall, it is an intersection of mathematics, statistics, and computer science. This field is essentially a new frontier in which there are a vast number of open problems, and it is an exciting time to get involved. For anyone interested in a career in data science, I recommend branching outside of mathematics and learning the basics of statistics and computer science. Traveling to data science conferences is an excellent opportunity to network and get a feel for the various work being done in the field. With respect to machine learning, learning how to use a programming language such as Python or R is essential.

Kathleen Daly

Staff Engineer Booz Allen Hamilton Lewis & Clark College BA Mathematics

I work in modeling and simulations, specifically radar modeling, for the consulting firm Booz Allen Hamilton using a specific computer model that the company created and has been maintaining for years. (If you want a clue how long the model has been around, it’s written in Fortran; there are periodic talks about upgrading to a different language, but it would be very costly to do so in terms of time and effort which is why no upgrade as of yet.) What it means for me personally that I work for a consulting firm is that other interested parties contract with Booz Allen regarding questions our model can answer, and then my group is tasked with using the model to answer those questions. My work generally falls into one of two bins: either developing new additions to the model, or running the model and analyzing the results to answer questions about specific scenarios. I fell into modeling and simulations accidentally; right after undergrad I was hunting for a job, and I knew someone who knew someone who was hiring. The position sounded pretty interesting, so I went ahead and applied, was hired, and, nearly five years later, I am still working for the same company in the same position. It’s a fairly challenging and consistently busy job, partly because modeling and simulations is often a time- and cost-saving measure. We might model, for example, how a particular jamming technique will perform against a particular radar because it’s much cheaper and easier to mock up the capabilities on a computer and get a look at the outcome than it is to build the jammer, build the radar, and run them against each other physically. Exactly how I spend my day depends on what kind of task I am working on at a given time. If it’s a development task where I am adding new capabilities to the 45

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model, that usually entails reading lots of documentation, perhaps on how a radar that we want to add to the model performs; adding code to the model to perform those functions; and then quite a bit of testing to make sure it’s working correctly. Analysis usually entails making sure the model will perform whatever functions are necessary to answer the questions posed: say, for example, flying an aircraft in a specific pattern over a ground radar; adding any capabilities that are missing; setting up the simulation; running it; and then double checking the outcome to make sure the answers are accurate and representative. Tasks might be quick questions that need to be answered within the week, but are more likely to be multi-month efforts where lots of data is eventually boiled down into infographics (usually made using MATLAB) and presented via PowerPoint. So on a given day I might be reading engineering documents, coding/debugging in Fortran, post-processing and looking at output, coding/debugging in MATLAB, making a presentation for the client, sitting in a meeting, or any combination of the above. While work is generally done on an individual basis, the environment is fairly collaborative. For example, I have a math background but little to no engineering background. If I run into an engineering concept I am unfamiliar with, it’s easy to grab a coworker that I know has some knowledge on the subject and ask them to explain. The majority of my coworkers have engineering backgrounds, with a smattering of mathematicians and physicists thrown in. Problem solving might involve algebra, trigonometry, calculus, statistics, matrix algebra, or just plain old logical thinking. Two of the most useful classes I took in undergrad are actually Statistics and Numerical Analysis, not necessarily because the subject matter covered in those classes was useful (although it was), but because both of those classes posed real-world questions that I would have to come up with a mathematical approach to tackle. And that’s really what I do now: given a real-world radar scenario, I come up with a way to recreate it using computer logic.

Joshua R. Davis

Lecturer in Mathematics, Statistics, and Computer Science Carleton College Oberlin College BA Mathematics and Computer Science University of Wisconsin – Madison PhD Mathematics

For a mathematician at a liberal arts college, my job is unusual, in that I spend only half of my time teaching. The rest of my time is filled with geology research. After college, I went to graduate school because I loved math. However, a couple of years after I earned my degree in symplectic topology, I found it difficult to make progress in that field. Around the same time, my wife, who is a geologist, tricked me into thinking about some of her modeling problems, by asking seemingly innocuous questions that were actually quite difficult. These problems turned out to be highly geometric in nature, and I was hooked. For example, several years ago I realized that some geologic data are best viewed as elements of the Lie group of rotations of three dimensional space, SO(3). I found that researchers in astronomy, medical imaging, robotics, and other fields had been doing statistics in that unusual setting for several decades. Their literature used lots of linear algebra, probability theory, and differential geometry, with a smattering of differential equations, algebraic geometry, Fourier analysis, etc. My math education enabled me to absorb much of this literature, add a few touches of my own, implement the ideas in software, and apply it all to problems that geologists care about. You could call this kind of work “technology transfer” between fields. My collaborators in geology, geophysics, statistics, and mathematics keep me supplied with more projects than I could ever finish. We attempt to fund those projects through grants, primarily from the US National Science Foundation. Whereas much of academic research requires narrow, specialized focus, my job instead requires broad, interdisciplinary curiosity. That suits my personality well, but there are some drawbacks. I don’t have the time to investigate any one idea 47

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as deeply as a specialist would. Sometimes I have to ignore an interesting topic, if it seems inapplicable or unfundable. Living off grants, even partially, requires an entrepreneurial, hustling mentality, which does not come naturally to me. As a lecturer, I have lower teaching and service expectations than tenure-track faculty. My wife’s work requires occasional long trips, and the flexibility in my schedule helps, whether our child and I accompany her or stay home. My advice to math students is: Don’t take categorizations such as “algebra,” “topology,” and “analysis,” or even “pure” and “applied,” too seriously. Interesting problems usually require a mixture of concepts from across mathematics. Learn broadly. Or maybe my advice is: the world is full of smart, thoughtful people with diverse interests and goals. Be receptive to them, and you might encounter some intriguing math unexpectedly.

Erick Deras

Lead Software Development Engineer The Rubicon Project Pomona College BA Mathematics and Computer Science

When I was younger, I always thought I’d work as a computer software developer or as a mathematical data analyst. I’ve since learned that the two fields nowadays tend to be more intertwined than most people realize. As I prepared myself to graduate Pomona College, I attended a career fair at nearby Harvey Mudd College in search of an interesting small up-and-coming company within some fastpaced dynamic industry to begin my professional career. This is where I discovered The Rubicon Project. The Rubicon Project is an online advertising automation tech firm. In brief, it does the following: for each person, for each device they own (e.g. computer, mobile phone, game console, billboard), for each ad space on a website or app they visit, a real-time auction is run consisting of over a million possible eager advertisers, each interested in different sets of variables. These variables – devices, websites, apps, advertisers, even government laws – all change as time elapses, leading the ad tech industry itself to also change, in a world that increasingly becomes more and more internet dependent. The industry is basically a giant operations research mathematical problem, in which each party involved has individual constraints as well as constraints against all the other parties. In addition, the problem subtly changes each time, trillions of times a day, but is expected to be solved within milliseconds every time (before the display loads its contents). I’ve been at Rubicon for over four years now. As part of the vital Ad Engine team, I flex both my computer science and mathematical skills when designing, implementing, and improving Rubicon’s filtering/probabilistic algorithms (based on statistical data) and auction behavior (first-price versus second-price). 49

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Typically, I lead three projects simultaneously, but am involved in a few others for support. Some days are more meeting-oriented, where leads from multiple teams (not all of them engineering) come together to propose, refine, or provide status updates for new and ongoing projects. Most days are quieter, with me doing research or actually implementing code changes. Occasional days of code deployments have me monitoring metrics, analyzing data to ensure sanity of revenue and ad render rates, or even beginning to plan possible future improvements. My role at Rubicon is a challenging and demanding position, requiring awareness, creativity, collaboration, meticulousness, and foresight. In the workforce I’ve come to realize that my previous formal education taught me how to effectively learn, how to ask meaningful questions, and how to quickly apply my new knowledge to new situations. These skills, plus being able to clearly document and communicate my thoughts to others, have yielded me a surprisingly huge amount of success, granting me three promotions within the first five years of my career. By no means am I perfect. I’ve had a few code rollbacks and projects that fell behind schedule, but I learn lessons from my mistakes to better my future strategies. Skills like those mentioned above are what most companies, especially tech companies, seek. They’re skills that I highly encourage others to ceaselessly practice, regardless of formal education level achieved, regardless of career or employment.

Lizette Ortega Dickey

Biostatistician Contract Research Organization University of Arizona BS Mathematics, Computer Science Minor University of Iowa MS Biostatistics

I am a biostatistician for a global contract research organization that supports the pharmaceutical industry. We perform clinical trials on medicines to get them approved by the FDA and other worldwide regulatory authorities to help patients who suffer from a wide range of diseases. Our clients and partners include pharmaceutical, biotechnology, medical device, academic and government organizations. I work with these sponsors as the lead statistician on several clinical trials. My mathematics advisor at the University of Arizona introduced me to biostatistics as a career. He said it was a growing field that would allow me to be easily employed, and I am happy to say that he was right. On a typical work day, I meet with either my internal project team or my external sponsor team where we provide updates on the ongoing clinical trials and answer questions. The remainder of my day is spent working on the clinical trials themselves. I work with programmers to provide output to our clients that are included in submissions to the FDA and the other regulatory authorities for drug approval. This requires several steps such as: writing statistical analysis plans; drafting specifications to guide programmers to produce outputs; and/or reviewing output provided by programmers to ensure accuracy before delivering to the sponsor. I also devote time to project management tasks, such as managing timelines and budgets. My work environment is very collaborative. For biostatistics and programming, we work in a team that typically includes a lead statistician, a senior reviewer, a lead programmer and a quality validator. Support team members are often brought in to relieve workloads and ensure timelines are met. I also meet with my line manager on a regular basis to review my work, evaluate my career growth, determine my training needs and assess my workload. One thing I appreciate about my company is their efforts to ensure their employees have a good work/life balance. They achieve 51

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this by regularly tracking and reviewing work assignments, as well as providing a competitive vacation policy. I routinely use mathematics and statistics in my daily work. Much of our analyses include logical derivations with the mathematical formulas behind those derivations. In addition, we use statistical hypothesis testing to evaluate two mutually exclusive statements about a population to determine which statement is best supported by the sample data. During my undergraduate studies, I enjoyed programming and chose to minor in computer science. This is applicable to my job since the mathematical equations involved in my work are programmed through statistical software. During my undergraduate studies, I was encouraged to apply to summer research programs. This allowed me to meet and learn from new people. You learn to work on projects with other team members, which helps you prepare for working in teams in the work field. I also received experience working on research projects. I feel like having this experience also helped me get into graduate school.

Alyson Doles

Research Mathematician US Army Corps of Engineers Engineer Research and Development Center Mississippi College BS Mathematics

In college, I did not know what career I wanted to pursue, so when it came time to pick a major, I simply chose what I was good at and what I enjoyed: mathematics. At the time, I did not realize just how open-ended that choice would leave my future career opportunities. This open-endedness, in my opinion, is the best thing about my job as a Research Mathematician for the US Army Corps of Engineers Engineer Research and Development Center (ERDC). A career fair my senior year of college connected me to this job, which has never pigeon-holed me into one area but rather has provided opportunities for me to explore several areas of interest, allowing me to discover my strengths and weaknesses, likes and dislikes. My branch within ERDC focuses on impact and explosion effects and is mostly comprised of engineers. I am one of two mathematicians in my office, and it can be intimidating not coming from an engineering background, but, as with all jobs, it is important to remember that there is a learning curve to be expected. The environment is one that encourages learning and professional development, and, although 80 to 90 percent of my work is done independently, almost everyone has an open-door policy which leads to mentorship and collaboration. No one is micromanaged, which fosters a sense of responsibility and allows the freedom to explore new methods and ideas. I have been given many opportunities to develop knowledge and skills in different areas within the realm of impact and explosion effects. I’ve been a project 53

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manager, designing experiments and overseeing field testing and data collection. I’ve been a code/program developer, using my background in computer science to write applications that facilitate data analysis. And I’ve been a modeler, setting up problems and running finite element code to predict and/or validate results from field experiments. I am typically only working on one or two projects at a time, so a normal day for me starts by picking up where I left off. For the most part, my work consists of some form of analysis or problem solving. There is always simple math and geometry in my work, but mostly it has just been the training that mathematics gives that has benefited me the most on a daily basis in my job: the ability to take a problem, break it down, think about it methodically, apply logic, and persevere to a solution. A college professor of mine once told me that an employer doesn’t often hire someone with a mathematics background to work math problems all day but instead for the way he/she thinks. Mathematics IS problem-solving. My advice to someone who wants my job or any job as a mathematician would be to realize that a mathematician will not necessarily do math all day. Mathematics is only the foundation on which one can build many careers. Therefore, find an application of interest for which to use your math training and enjoy the journey!

Samantha Drost

Senior Analyst Business Intelligence and Analytics Target Corporation Augsburg College BS Mathematics BA Economics

I always had a passion for math and science from a young age but I never really knew what I could do with it when I graduated, besides teaching. I entered my freshman year of college wanting to be a chemistry teacher. My plans dramatically changed after sustaining a spinal cord injury while boogie boarding in the ocean on a family vacation the summer before my sophomore year, leaving me a quadriplegic. Since I was physically unable to participate in the lab part of science due to my new physical disability I shifted my focus to mathematics, which I was able to do completely via voice dictation software. It wasn’t until an internship during my junior year of college at Target Corporation that I was exposed firsthand to all the career opportunities for someone with a math major. I have now worked at Target just over six years in a variety of roles. The majority of them have been focused around merchandising and marketing analytics with a focus on the guest. One of my first roles was on the Merchandising Testing Team in which we designed and recapped tests for different store initiatives. My background enabled me to understand how to set up tests that would yield statistically significant results, including making sure to pick a large enough sample size, being aware of any bias in inputs, and accounting for the effect of seasonality in trends. Besides setting up the test themselves, being able to recap and pull out actionable insights from the data was a large part of my role. Currently, I help support the Marketing Loyalty Analytics team doing analytics on marketing campaigns and channels. I spend the majority of my days working in 55

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the agile method (a popular approach to software development) alongside a team of other analysts. Day-to-day, a large portion of my role includes identifying data and querying from large databases before I’m able to do any type of analytics. While I didn’t have much computer programming experience from college, my background in mathematics gave me the ability to think analytically and pick up programming on the job. Overall, I strongly believe my background in mathematics helped shape a solid backbone for my analytical career. I’ve been able to learn on the job additional skills to help execute my analysis, including business acumen and technical skills like coding. Data analytics and data science jobs are growing in demand and are a great fit for those looking to utilize a mathematics degree.

Kate Dyson

Partner White & Case LLP Carleton College BA Mathematics University of Minnesota Juris Doctor

I am an attorney, specializing in defending companies which are being investigated by the government for alleged violations of the False Claims Act (e.g., making a claim for payment from the government that you are not entitled to, but it is quite complex). I also do antitrust work, and have devoted a significant amount of time to pro bono work (providing legal services to those who could not otherwise afford such services), most notably successfully representing a man in an Innocence Project case, and getting him out of prison after he had served 23 years for a murder he did not commit. The bulk of my work is for healthcare-related clients, including pharmaceutical companies, manufacturers of medical devices, and providers. After college I planned to go to graduate school in math, but wanted to take a year off before applying. In that year, I went to work for the New York City Department of City Planning, planning bicycle and pedestrian paths and routes. I enjoyed this job very much for a few years, but then wanted something that was more analytically rigorous, but not a PhD program. I opted for law school, with the hope that it would allow me the opportunity to write more, use intellectual rigor, and help people. Overall, I have met those goals in my career as a lawyer. I have found that being a math major has opened doors to me that otherwise might have stayed shut given that I did not go to one of the most elite law schools; the person who hired me for my current job told me that I was one of the only people he had ever hired from a non-top-ten school, and part of the reason was he was confident because of my degree in math that I had sufficient attention to detail. All of that is to say, a degree in math makes people think you are smart (and you are—but so are a lot of other people with degrees in other subjects). Being a math major helps me attack a problem logically and analytically examine how the facts of a given case fit into the legal framework. It has also allowed me 57

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to step in boldly when dealing with financial issues, technical issues, and experts, all of which come up in every single case I deal with. Being able to converse easily with statisticians who are analyzing a client’s Medicare payments is incredibly valuable for understanding case issues, and thus for helping my clients. The same goes for being able to read a balance sheet. Being a math major not only helped prepare me to do these things, it also gave more senior attorneys and our clients confidence that I could handle the issues. However, my use of mathematics just touches the surface of how you could use it; I have colleagues who do a great deal of work investigating alleged financial fraud and who advise banks on tax and other financial issues, and facility with numbers is invaluable there. I do not have a typical day, but I spend the vast majority of my time communicating, including through email, briefs to the court, calls with clients, and meetings with colleagues. An ability to clearly communicate sound ideas is a core skill of being a successful lawyer. I see a lot of bad writing, and a lot of poorly constructed arguments, and truly value junior lawyers who can form a cogent argument and communicate it succinctly and persuasively. While there are definitely ways to be a lawyer who works 9-5, most attorneys I know work fairly long hours. I have been fortunate in my colleagues, and thus am able to walk my son to school and eat dinner with my family most nights. That said, I typically log back on and do more work after my children are asleep. I have noticed that (at least based on the experience of my family and friends) this schedule is fairly typical of many jobs.

Berton Earnshaw

Director, Data Science Research Recursion Pharmaceuticals Brigham Young University BS Mathematics MS Mathematics University of Utah PhD Mathematics

When I finished my Masters degree in mathematics at Brigham Young University, I was newly married, and my wife was expecting our first child. At the same time, my parents were about to begin an assignment to preside over the Brazil Porto Alegre South mission of the The Church of Jesus Christ of Latter-day Saints, and they offered to let us live in their home in Park City, Utah, and to work for my father’s software company, LifeLink Corp. (now EbixLife Inc.), while they were away. As parents-to-be, the security of a job and home was very appealing, so we gladly accepted. However, after only a few months of working in the “real world” we decided that I would apply to PhD programs, and by the end of the next summer, I was a student again, studying math biology at the University of Utah. I successfully defended my dissertation three years later, and immediately started a National Science Foundation IGERT postdoctoral fellowship at Utah. (NSF IGERT was a program focused on interdisciplinary collaboration and training.) Two years later I took a Visiting Assistant Professorship at Michigan State, but only after turning down a job offer doing machine learning for a local Utah company. At the time I did not know much about machine learning, and felt that I wanted to work in academics anyway. At first, my wife and I were excited about being at Michigan State, but the combination of a growing family (we had three of our five children by then) without the growing salary, the dismal prospects for tenure-track positions at the time, and being a long way from family and friends in Utah, caused us to consider other options. I received job offers, including another from the same Utah-based company 59

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that had previously made me an offer, but decided instead to start a new company with two partners in Utah. We called the company Perfect Pitch Technologies, and we developed call center software for off-shore call centers. At the time, I knew very little about call centers and creating complex software products, but I was eager to learn and take on a new and risky challenge. For more than two years I worked long hours building our business, and I did indeed learn a lot about writing software, maintaining hardware, and managing people. However, the job was never the right fit for me – I was not doing much math, and I wanted to build more than call center software. So when the same individual who had twice offered me a job contacted me again and asked me to help him launch a new machine learning start-up, I heartily accepted. I joined the founding team of Red Brain Labs LLC and immediately began working on software – for call centers! But this time it was a machine learning product for optimally matching callers and agents. So I was doing math again, gaining valuable experience with machine learning, and honing the programming and management skills developed while at Perfect Pitch. Our small team of engineers worked long and hard on our call center optimization product, and within a couple of years we had been acquired by Savvysherpa Inc., a privately-owned healthcare research and development company based in Minneapolis, Minnesota. At Savvysherpa, I was both a Principal, helping shape the strategic agenda for the company, and a Senior Scientist, working with other Senior Scientists to create and maintain the research agenda for the company. I developed research programs that applied machine learning, signal processing, and optimization to healthcare problems, e.g. remotely managing chronic diseases and discovering disease progression pathways from insurance claims and electronic medical records. This was an invaluable opportunity for me to learn to apply machine learning and statistical testing to problems beyond call centers and to work directly with physicians and healthcare executives in creating and executing programs that benefit patients. Recently, I accepted an offer to join Recursion Pharmaceuticals as Director of Data Science Research. Recursion is a biotech start-up that combines experimental biology, bioinformatics, and machine learning to discover new therapeutic opportunities for rare diseases. I lead the data science research team in applying deep learning to images of cellular disease models. The data science problems at Recursion are exciting and challenging, and the opportunity to work to improve the lives of those suffering from rare genetic diseases is very motivating. Our large image datasets provide a chance to apply very modern deep learning techniques and work with deep learning luminaries like Yoshua Bengio, a member of our Scientific Advisory Board. Recursion’s goal is to treat 100 diseases by 2025, so check in with me then to see how we did.

Chandra Erdman

Senior Solutions Consultant Google, Inc. Augsburg College BA Mathematics Columbia University MA Statistics Yale University PhD Statistics

I’ve always loved math – especially the fact that if I work long enough and hard enough, I will get to the right answer. I’ve always felt most comfortable dealing with things that are objective. Growing up, I had no idea of the opportunities that a mathematics degree would offer me. My world was very small, but math changed my life. Today I’m a Senior Solutions Consultant for Google, and I use math every single day. Although I found math challenging, it always made sense to me, so I decided to major in it. It turns out that once you earn a mathematics degree, you get recruited for all sorts of things. I was a couple of years younger than my peers and I didn’t feel ready to leave the safe space of being a student, so I was very open to learning about opportunities for advanced degrees in the mathematical sciences. I was incredibly fortunate to be nominated and accepted into the McNair Scholars and EDGE programs; these gave me the resources and social support to pursue (and get through!) my PhD, which I received from Yale University. (These programs help strengthen the success of women and underrepresented groups in graduate school; learn more at mcnairscholars.com and edgeforwomen.org.) The most important thing I learned at Yale was that while I understand theoretical concepts, I get the most joy from applying math in ways that help people. For example, I built a software package that is used in all kinds of ways: to study cancer, financial markets, and even climate change. And when people make discoveries using my software, I get notified: talk about gratifying. My first real job with a PhD was with the US Census Bureau. I was part of the Center for Statistical Research and Methodology. In that role, I consulted with other federal statistical agencies and came up with more efficient methods to make estimates. When most people think of the Census Bureau, only the decennial 61

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census comes to mind. What they don’t know is that nearly every day of the year, approximately seven thousand Census Bureau interviewers are knocking on doors, collecting data to estimate everything from childhood obesity rates to the monthly unemployment rate. Although my world was very small growing up, my role at the Census Bureau gave me the opportunity to travel the world to discuss methods with statistical agencies of other nations. Some of my favorite experiences were in Iceland, the UK, and Brazil. Now I’m at Google where I study user feedback for two of our biggest products. I look at usage data and actual written feedback to understand what users like and don’t like and what we may want to change. Sounds simple, but each of these products has over a billion users! I’m on a team in which everyone is performing the same function (studying user feedback) but we’re each working on one or more different products. Even though our products don’t overlap, we spend a lot of time talking with one another about how we’re doing what we’re doing. I really enjoy these conversations and can easily lose track of time talking about statistics. I also enjoy collaborating with people on my two product teams (Google Search and Google Chrome). I spend about a third of my time in meetings with representatives from a wide variety of functions (marketing, analytics, engineering, sales, etc.) talking about everything from specific usage statistics and product experiments to global strategy. I credit my mathematics education with putting my life on a whole new trajectory. I hope to inspire and mentor the next generation of mathematicians, especially those from underrepresented backgrounds.

Katie Evans

Professor of Mathematics and Statistics Associate Dean of Strategic Initiatives Director of Integrated STEM Education Research Center Louisiana Tech University Morehead State University BS Mathematics Virginia Tech PhD Mathematics

When I was growing up, my favorite classes were math and English. In high school, the accomplishment I felt after writing an essay about some English classic was the same sense of accomplishment I felt when I got to the end of a one-page calculus problem. My high school calculus teacher tried to talk me into taking the AP exam, but I told her I didn’t want to because I knew I wanted to take calculus in college, and I was nervous about starting out in Calculus II. I started at Morehead State University as an accounting major with law school visions in my head. At the time, business majors were not required to take calculus, but I begged the math department chair to let me in his already full 8:00 a.m. calculus class. That was possibly a life-changing moment. If I hadn’t gotten into calculus my first semester, I would have probably just settled for filling my schedule with more business classes. I may have never tried to get into another calculus class. But that was not to be! Instead, I continued taking math classes and decided to drop my advanced accounting course when it was taking too much time away from my introduction to proofs course. I truly had no idea what I could do with a math degree, which scared my family to death. But, I trusted my teachers and advisor who assured me that I could get a non-teaching job with a math degree, because I had no interest in teaching. With the encouragement and support of the Morehead State Mathematics and Statistics faculty, I secured positions in two Research Experiences for Undergraduates and one Undergraduate Research Semester program at Los Alamos National Laboratory (LANL). While at LANL, I worked on a project for the FBI concerning a purely voice-based technique for lie detection. The semester spent at LANL was a life-changing event. While I had 63

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already been applying for graduate programs, the experience at LANL solidified in my mind that I wanted to do research in applied mathematics and pursue a PhD. After graduating from Morehead State, I started my graduate work at Virginia Tech in 1999. As a teaching assistant, I had the opportunity to teach calculus classes with full responsibility. I fell in love with teaching and realized that I wanted to teach college-level mathematics upon completion of my degree. I was a PhD student in the Interdisciplinary Center for Applied Mathematics, and my dissertation was in the area of design and simulation of low-order controllers for systems governed by partial differential equations. In order to add an experimental dimension to my research, I accepted a postdoctoral position in Mechanical Engineering at Oregon State University. I worked with an aerodynamicist on modeling, control, and simulation of unmanned micro air vehicles. After my postdoctoral position, I accepted a tenure track Assistant Professor position in mathematics and statistics at Louisiana Tech University, where I have been since. I am part of a college that is built upon an interdisciplinary approach to research and education, which aligns well with my passion for applications of mathematics. I have had the opportunity to teach undergraduate and graduate level mathematics and engineering courses. My research program has expanded to include simulation and controls for micro air vehicles and for biomedical engineering applications as well as STEM education research. To date, I have graduated five PhD students and been a part of securing over 11 million dollars in external funding from the National Science Foundation, Air Force, and Louisiana Board of Regents. Perhaps the most important byproduct of my education and training in mathematics is that I learned analytical thinking and problem-solving, skills that translate across many fields and professions. These skills equipped me with the tools necessary to steer my career trajectory as I discovered my passions and to respond to opportunities as they arose, including a move into academic administration.

Jaquelyn Fernandez Rieke

Founder Nutty Steph’s Land Steward Onion River Campground Carleton College BA Mathematics

It wasn’t until late sophomore year after trying on philosophy and then English that I chose to study mathematics. I chose it in an instant, after a woman told me she was majoring in math and it sounded so cool coming out of her mouth. She wore red lipstick and no shame; not even a slightly naughty deviousness, which is how I felt at the thought of it. It seemed bold to allow myself to play for three years that intimate sharpening game with my mind. It felt indulgent and unabashedly smart. My decision was sealed. Prior to college, I had liked and succeeded in math but hadn’t considered it for a course of study, nor did I have any particular reason to do so. After declaring it, though, there emerged a steady stream of unexpected ways that my math major would serve me; reasons even beyond being cool. (Although the panache of the title does indeed add depth to my professional first impressions!) For one thing, math was something I would not learn without a teacher. I realized that whereas most other subjects were things I could independently pursue through books and travels, an abstract exploration of the phenomena underpinning our universe was relatively unique to the classroom setting. After my graduation, I became a high school teacher. I did not teach for long, but I did develop a passion for the math curriculum. Following my short teaching stint, and being generally unable to fit comfortably in any institution, I succumbed at twenty-three to a destiny of self employment, to building my own universal laws about the value of my efforts and time. I started making my own granola and peddling it around Vermont, and then bought a chocolate factory, and then bought a campground, and then built an events business, all on wings and prayers and by the skin of my teeth. Within and through these endeavors, I carve out opportunities for political activism, botany and farming, mentorship, and community expansion. 65

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My work and life are interwoven like a rich and sturdy fabric, and I enjoy a place of leadership in my community as a result of the risks I have chosen to accept. Once, I randomly met one of my granola customers who happens to build radically innovative software for classroom math education. My explosion of enthusiasm upon learning of his work led him to contract me. I worked for several years on his federally grant-funded projects, which brought me good earnings and deep satisfaction. It’s been a rambling road, my career, and beautiful. As it turns out, I am always a mathematician at heart, balancing the equation of profit viability equals not causing harm. I move money constantly between customers, investors, vendors, employees, and bank accounts in a cashflow-balancing circus of modern commerce. Good business is no longer just about the persistent cheapening of Earth and the laborers. When there are profits, I tend to divert them to resources that are human, environmental, culinary, or cultural: source an ingredient more expensively from a more responsible grower, increase the paid leave benefit to workers, assume the up-front cost of training a co-worker with Down’s Syndrome, prematurely buy land so as to build rich soils without delay. I think of myself as a servant to those whose money I move around, and it is only with careful calculations that I am able to serve them responsibly. I spend days with people, finding out what they need to succeed. I spend nights with my spreadsheets where I tinker and imagine, exploring how to provide for those needs. This is a lonely journey, though, where the one individual holds the purse strings for many. Now my goal is to sell my chocolate and granola business to the workers, dissolving my corporation and erecting in its place a worker-owned cooperative, for which I would be among the workers. This requires financial literacy for everyone. We meet monthly for an all-worker finance review, and each person attends voluntarily, unpaid. This time serves as an entryway investment into what will soon be theirs, or rather, ours. Ours to count and divide; ours to ponder and realize the value of Earth and our labors. Most of our monthly review meetings reduce me to tears, a combination of joy and relief. I am weaving my way toward the absolute value of my destiny, toward educating without insecurity, toward a way of affecting change in our society, toward yet still unearthing reasons for my mathematical background, which began when it sounded so cool in the mouth of a lipsticked woman.

Stephanie Fitchett

Statistician and Data Scientist Transamerica Life Insurance Company University of Nebraska–Lincoln BS Mathematics MS Mathematics PhD Mathematics Colorado State University MS Statistics

When I started college, I had no idea what I wanted to do. Everything was interesting – I took classes in literature, history, economics, architecture, music, chemistry, mathematics, and foreign languages. Mathematics as a major was almost accidental, though I had always enjoyed mathematics and problem-solving. My first abstract algebra course is what really hooked me, and led me to graduate school. My early career followed a traditional academic path, and I joined the faculty in a small honors college, where I loved teaching bright undergraduates in an interdisciplinary setting. Trained as a pure mathematician, with a limited background in statistics, I wound up teaching the only statistics courses on campus. Both colleagues and students doing research in a variety of disciplines sought statistical advice I did not feel well-qualified to provide, so I spent a sabbatical studying statistics. Eventually, I decided I wanted to spend more time doing statistical work, and moved from academia to industry. My first non-academic position was in the Statistics Group at Sandia National Laboratories (Albuquerque, New Mexico), which was essentially a statistical consulting role in which I supported a wide variety of projects across the Labs. I later moved to Neptune and Company, an environmental consulting firm in the Denver area, where I did environmental statistics, and more recently to my current position at Transamerica Life Insurance Company, where my title is Data Scientist. When looking for positions outside of academia, I was pleasantly surprised to find that potential employers had a high regard for degrees in mathematics. For instance, at Neptune, over one-third of the technical staff had a degree in the 67

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mathematical sciences. On my current Advanced Analytics team at Transamerica, five of the nine Data Scientists have degrees in mathematics, statistics, or both. So what do I actually do? At Neptune, our projects involved multi-disciplinary teams, so I interacted with engineers, risk assessors, hydrogeologists, programmers, soil scientists, and other statisticians. I supported risk assessment, which attempts to quantify the impacts of environmental contaminants on human health and health of ecological systems. Risk assessors traditionally use deterministic equations with conservative inputs to estimate potential risk to a human receptor or an ecological system. Statisticians working with risk assessors are able to establish realistic (rather than overly conservative) estimates of risk, with associated estimates of uncertainty, which provide better information for decision-makers. As another example, I developed sampling designs and performed data analysis for sites that had been contaminated and were undergoing remediation efforts, with the goal of understanding how well those remediation efforts were working and if additional remediation would be needed. At Transamerica, much of my work is again focused on risk assessment, but now on mortality risk associated with underwriting life insurance policies. My work includes managing very large datasets using cloud-based tools and creating predictive models that support facets of the underwriting process. My team works on a wide variety of other projects, using natural language processing to understand the reasons clients contact our call center and forecasting retirement readiness for our institutional clients’ employees, for instance. The variety in my work and getting to work on interesting problems with great people from many disciplines are my favorite things about being a statistician and data scientist. Asking good questions and effectively communicating statistical ideas to other bright, technically oriented people are important aspects of my job. Communicating with internal and external clients, who are often less quantitative than my immediate colleagues, is also important. For those interested in statistical positions, take some statistics courses, learn to program (the specific language isn’t so important, but being able to write code to organize and compile data, create visualizations, and run simulations *is* important), learn about databases and basic querying languages, take a technical writing class, try some science/engineering electives, and find an internship (the national labs have terrific opportunities for students!). Mathematicians who also have practical experience with statistics are in demand!

Kathie Flood

CEO Cascade Game Foundry SPC Senior Program Manager Lead Microsoft Games Studios Central College BA Mathematics and Computer Science Drake University MA Journalism and Mass Communications

Making a video game is an odd mixture of science and art, and running a small business is a flat-out goat rodeo—throw them together and you never know what problem you’ll be asked to solve next. The charm and challenge of ambiguity is why I love my job as the CEO of Cascade Game Foundry SPC. The best word to describe my career path is probably “accidental.” I didn’t have a major picked out until my junior year in college. I dumped way too much money into arcade games back then, but it didn’t occur to me that you could get an actual job working on games. I knew I wanted to work on fun, challenging projects with smart people, but that’s about it. My first job was as a technical writer responsible for documenting operating systems’ applications program interface sets, so I described how operating system function calls worked and wrote sample code that exercised those functions. After several years of this, I realized I wanted to be closer to the nose end of the dog, rather than the tail, so I moved into Program Management to be part of the design and development process. I was in the right place (Microsoft) at the right time (mid-90s) with the right skills (technology background, project design and management experience) and interests (sports) when Microsoft decided to get into the entertainment software business. As a Program Manager, it was my responsibility to drive the creation and maintenance of a game’s vision, feature set, and schedules, as well as deliverables and trade-offs from project inception through launch. That included coordinating the work of functional leads and team members from Game Design, Development, Art, Audio, Testing, Product Support, User Experience, Localization, Business Development, and Marketing. After over 14 years working on PC and Xbox games for Microsoft, mostly in the sports, racing, and simulation genres, I left to start my own company, Cascade 69

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Game Foundry SPC. We are a small, independent game development studio specializing in PC and virtual-reality simulations that help people explore the world. Our flagship product is “Infinite Scuba,” a diving simulation game in which players do what real divers do: identify wildlife, find artifacts, collect branded scuba gear, and take photos to share with friends, while learning about dive science and the local culture, history, and environmental issues of the real-world dive sites in the game. SPC stands for “social purpose corporation,” also known as a “B” corporation, which means we support a triple bottom line: people, planet, and profit. Our social goals are environmental education and the promotion of STEM skills. We make our games available free to teachers and schools, and we donate a portion of our revenue to ocean environmental non-profits. My mathematics background is instrumental for me in two ways. First, I have a strong understanding of the higher-level mathematics required to provide realistic physics and next-generation 3-D graphics in today’s games and virtual reality experiences. This enables me to work effectively with the programmers and artists responsible for these features, anticipating and understanding their challenges. Second, the problem-solving skills I learned while studying mathematics and programming are absolutely invaluable as a software developer and a small business owner. Much of my ability to break complex issues into solvable pieces, find creative solutions, and execute methodically, I credit to my mathematical education. There are possibilities of career advancement for people managing video game production. At a large company like Microsoft, one can climb the corporate ladder to achieve positions such as Group Program Manager, Studio Manager, General Manager, etc. However, I preferred to focus on a single game and work with a dedicated team to make a creative vision come to life. That focus on the detailed end-to-end process of game creation ended up being critical when I started my own company. At large companies, the bench tends to be deep, enabling people to become specialists in fairly narrow areas of expertise. At small companies, the bench may not exist at all, so people need to be utility players with a wider range of skills and the willingness to learn skills (or wing it) outside of their current expertise. Not climbing the corporate ladder also enabled me to have a vibrant life outside of work, which is more difficult to do the higher you climb in management. (My husband and I are avid musicians, scuba divers, and bicyclists.) Running my own small business also enables me to craft our virtual travel experiences for broad audiences, targeting older people, women, and others who might not consider themselves gamers yet. When people ask me what the most enjoyable aspects of my job are, I sometimes ask them how much time they have. I thrive on bringing order to chaos, and that definitely describes the process of creating a game and running a small business. It’s also very gratifying to see people have a good time playing your finished game. Recently, an older woman who could no longer dive in the real world tried our virtual-reality scuba dive in Belize. When she took off the headset, she had tears in her eyes. She smiled, gave me a hug, and said “That was amazing! I thought I would never experience that again. It was so beautiful. Thank you!” I never got that kind of reaction when I was writing technical reference guides for programmers.

Tamara Fuenzalida

Instructor of Mathematics Tarrant County College Northeast Tarrant County College AS Mathematics Texas Christian University BS Mathematics MS Mathematics

I recently achieved my dream of becoming a mathematics instructor at Tarrant County College. I have always wanted to teach, but a career in education requires, well, an education, and I was not able to go to college right after high school. Instead, I started a family and had to work. Several years and many unfulfilling jobs later, I finally decided to go back to school and enrolled as a part-time student at Tarrant County College. My goal was to get a degree so I could teach something somewhere. I wasn’t sure what, and I didn’t know where, but just getting back to school was a step in the right direction. I started out slowly, and skeptically. Working full-time, keeping up with three kids, and studying was challenging to say the least. I honestly thought it was more than I could handle, but I soon discovered the key to academic success: the professors. Who knew?! I spent a great deal of time in office hours, speaking with professors, getting help with assignments, discussing career goals, and receiving advice and encouragement in general. I was blown away by their confidence in my ability to succeed. I realized that without their support, I would have dropped out, and that’s when I realized I wanted to be a teacher at Tarrant County College; I wanted to help students like myself succeed against the odds and achieve their dreams. To this end, I quit my job and accepted a position working in the TCC Math Tutoring Lab. I worked with students in classes ranging from developmental math to Calculus III, and it was so much fun! I loved finding ways to help students learn new concepts. I also discovered that mathematics is the primary stumbling block that prevents many students at the community college from earning a degree. That, more than anything, spurred my decision to teach mathematics. If I could 71

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help students learn math, I could help them graduate and get the jobs they wanted. After that, I spent a great deal of time in the math department, discussing my goals and developing a plan to become a math instructor at TCC, which included a master’s degree. With the help of my mentor and several recommendation letters from other professors, I was awarded a transfer scholarship to Texas Christian University. My experience at TCU was extraordinary. I spent most of my time in the mathematics department, and, once again, the faculty proved to be the key to my success. I worked very closely with my professors there, and with their help and encouragement, I completed a Bachelor of Science in Mathematics and a Master of Science in Mathematics, exactly what I needed to become an instructor at the community college. Soon after graduating, I applied for the coveted Instructor of Mathematics position at Tarrant County College, and with the help of glowing recommendations from my TCU and TCC professors, I got the job! Some of my duties include reviewing textbooks for future courses and serving on various committees to improve administrative processes, such as enrollment and the role of placement exams. My primary duty is teaching five courses each semester. I plan the schedule for each class; write syllabi; develop lessons for each class; write, proctor, and grade exams; give lectures; and track grades and attendance for each course. Mostly, I am helping students learn math. It is what I have dreamed of my entire life and for the first time, I can take satisfaction in my work. To any students interested in pursuing a career in academia, I recommend working closely with your professors. Get to know them and seek their guidance – they hold a wealth of experience and knowledge, and they want to help their students succeed.

Angela Gallant

Mathematics Instructor Inver Hills College College of Saint Benedict BA Mathematics University of Kentucky MS Mathematics

As most readers are certainly familiar with the field of teaching, having participated in the educational process for years and years, I will focus primarily on what it is like to teach at the community college level. First of all, I will fully admit that although I always (at least since the age of 8 years old) dreamed of becoming a math instructor, it was not until I was in a temporary position at Ridgewater Community College that I considered the possibility of teaching at a two-year school. Having had a wonderfully enriching and engaging experience as a math student at the College of Saint Benedict and Saint John’s University (as well as being involved in the Summer Mathematics Program at Carleton College and participating in Budapest Semesters in Mathematics), I imagined myself having a career teaching at a four-year liberal arts school after completing my doctoral work. As a graduate student at the University of Kentucky, I found my coursework fascinating. I even enjoyed preparing for qualifying exams. I especially enjoyed the chance to teach my own courses (not simply as a teaching assistant)—College Algebra, Calculus I, Calculus II, and Calculus III. After earning my master’s degree, qualifying as a doctoral candidate, and beginning research in the field of complex analysis, I began to be less sure that I was interested in a career in which research would be among my job expectations. As luck would have it, I was offered a one-semester position as an instructor at Ridgewater Community College in my home town of Willmar, Minnesota, filling in for an instructor who was needing emergency knee surgery. Knowing nothing about the community college system, I was hesitant to just abandon my graduate studies. But the University of Kentucky was kind enough to extend an offer to allow me to continue my studies where I left off should I decide to return after taking the job for a semester. 73

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I came to discover that the two-year college teaching experience was exactly what I was looking for. It has allowed me to teach a wide variety of courses: remedial algebra, the Calculus sequence, Math for Liberal Arts, Statistics, and Linear Algebra. In addition, I have had the chance to teach courses in a variety of formats: traditional, hybrid, and online. My focus is on teaching with no expectation of research or publication. My workload is fifteen credits per semester, which usually equates to between three and five courses, more than is required at a typical four-year liberal arts school. The thing I appreciate most about working in the two-year college system is the wide variety of students with whom I have the opportunity to work. There is hardly a typical community college student. I have students straight out of high school, parents who are returning to school after they have spent years raising their children, and adults who are returning to school looking for a career change or advancement. I have even had a student who was a grandparent looking to brush up on his Calculus so that he could help his grandson with the subject. Many of my students are first-generation college students. Some of them are taking the minimal amount of math they can to get by, whereas others find a passion for the subject while they are here. In the fifteen years I’ve been teaching here, we have had several students who have gone on to eventually pursue graduate studies in mathematics. If you find great joy in the study of mathematics and in teaching mathematics, but feel less than thrilled at the idea of doing research in mathematics, teaching at a two-year school could be a nice option for you! If this is something you’re considering, look for a graduate program that will allow you to teach your own courses as a graduate student and consider seeking out teaching and tutoring opportunities as an undergraduate as well.

Skip Garibaldi

Director IDA Center for Communications Research La Jolla, California Purdue University BS Computer Science and Mathematics University of California, San Diego PhD Mathematics

In my previous career as a math professor, I sometimes felt less like a lab scientist and more like a poet. I mostly proved theorems alone (my collaborators were far away so we worked by email), I did not have expensive equipment to buy and a lab to fill with students, and I could do my work almost anywhere. Taking this analogy further, I also wondered: how do my journal articles make my readers feel? Are my readers happy? After I started working with the Department of Defense, I didn’t have these questions. When you make progress on their problems, there is no question that someone cares. And the work environment is highly collaborative. Experiencing this opened my eyes to a different sort of mathematical career, and today I work at the IDA Center for Communications Research in La Jolla, a federally funded research and development center (FFRDC) that solves problems for the DoD. Most of the researchers in my office have a PhD in pure mathematics. They work in self-organized groups on a variety of problems of interest to the DoD, and the result of their work is usually a math paper or prototype-quality software. The work atmosphere is friendly and welcoming: if you ask someone what they are working on, they are usually happy to explain it, because for them the best outcome is if you join in the project and help out! And, because new problems are always arriving, researchers are encouraged to learn new subjects. This career-long scientific growth is one of the attractions of working at the Center. A typical day for a researcher at the Center usually involves going to a math talk or two, working on research – proving theorems or coding up experiments – and talking about math with other researchers. In that sense, our office feels like a mathematics department at a high-end research university, albeit an unusually collaborative one with no students. 75

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What can you do to lead to a career as a mathematician contributing to national security? Like with many industries, an internship while you are still in school is a great way to see what the job is like first-hand. As a math student, the easiest place to start might be one of NSA’s paid summer internships – Google can help you find more information. If you are already a professor and are reading this, CCR organizes every summer a research program for faculty called SCAMP (some people describe it as “an REU for professors”) that is a great way to see how you might fit in. You might wonder about what classes to take. I suggest amassing technical depth, because there is no substitute for it, and your student years are a great time to focus deeply on something. Also, it’s really useful to learn how to code, even for pure mathematicians. Coding may feel daunting when you first try it, but it’s not that hard to become moderately competent, and even that modest level of mastery can pay dividends in many parts of your career. Finally, check out the Putnam Competition. Practicing for and taking this type of exam can provide valuable cross-training. These are things I would recommend for any student aiming to pursue a career based on a PhD in mathematics. When I started as a professor, I never guessed that there were such engaging and collaborative job opportunities for mathematicians working in national defense.

Sommer Gentry

Mathematics Professor United States Naval Academy Stanford University BS Mathematical and Computational Science MS Operations Research Massachusetts Institute of Technology PhD Electrical Engineering and Computer Science

I use math to save people’s lives, by applying mathematical optimization and simulation to get people the organ transplants that they need. My field is Operations Research, which is the discipline of applying advanced analytical techniques to help make better decisions. I chose Operations Research because I have a flexible toolkit for discovering how governments, businesses, and humanitarian organizations of all types can achieve their goals, which means I get to learn about something new with every project. When my husband, who is a transplant surgeon, came to me with a puzzle about how to match donors and recipients for kidney transplants, both of us realized we were uniquely positioned to make a difference in transplantation. Working with my husband means building models to answer the most important questions in transplantation. Sharing intellectual excitement about our research makes us love each other more, because we are constantly reminded of and working to develop each others’ talents and achievements. Kidney exchange lets living donors give kidneys to a loved one, even if they are incompatible with that loved one. We find compatible exchanges, matching one donor and their intended but incompatible recipient to another pair with a complementary incompatibility, so that two compatible kidney transplants result from exchanging kidneys, and two people who would otherwise not donate become living donors. This is actually a mathematical optimization problem! I wrote software that the United Network for Organ Sharing uses to determine which pairs 77

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should exchange with which other pairs so that the largest number of transplants will be possible. I also work to reduce geographic disparities in liver allocation. There are eight regions used to distribute livers from deceased donors in the US, but these regions are very unequal in their balance of demand and supply of organs. I designed new boundaries for geographic areas that would result in more fair distribution of livers. The math is similar to what would be used to gerrymander voting districts, but our goal is to get life-saving transplants to the patients who need them most urgently. Persuasive writing and speaking are the skills which matter most in getting the results of my models into actual practice. To make a difference, I must work closely with transplant policymakers to ensure that their values and concerns are accurately reflected in the equations I choose. In writing grants and papers, my task is to convince readers that the studies I have performed or want to perform are valuable and relevant. I am a civilian math professor at the United States Naval Academy. I want to show students how they can make the world a better place with mathematics, and optimizing transplants is a concrete and vivid example of this. I love to draw connections between my experiences in making transplant policy and the math I am teaching, which might be combinatorics or decision trees or calculus. Many of my students volunteer to do honors and independent research projects with me; they learn about discrete event simulation, about integer programming, and about how to read and write scientific reports. Their efforts contribute to the larger goals of improving transplantation.

Jennika Gold Thomas

Director of Strategy, Fixed Income Analytics FactSet Spelman College BA Mathematics, minor in Spanish MS Mathematics Carnegie Mellon University MS Computational Finance

I have had a lifelong affinity for mathematics. As a child, I loved numbers so much that my nickname was “County,” in honor of me counting all objects around me. As I began my collegiate studies, a major in mathematics was a given. A career selection however, was a different story. I was interested in the practical application of mathematics, outside of academia, and set out to find a suitable applied math field. Several college internships exploring various industries and applications of mathematics, including engineering at NASA, actuarial science at Minnesota Life and private wealth management at Goldman Sachs, eventually led me to quantitative finance. Working on Wall Street at such a young age, I quickly surmised that further education was needed to distinguish myself and to qualify for the modeling work that piqued my interest. Directly after my MS in Mathematics from Spelman College, I completed Carnegie Mellon University’s Master of Science in Computational Finance program and established a solid grounding in finance to complement my mathematical background. The courses in interest rate modeling, financial products, programming, and statistical and time series analysis provided a strong educational foundation in quantitative finance. I started my full-time career as a trader and financial engineer at Goldman Sachs. In this role, I worked with and enhanced algorithmic trading models and processes on the trading desk. I later transitioned to Derivative Solutions (a boutique fixed income modeling shop) as a quantitative analyst and financial engineer. Shortly thereafter, FactSet acquired Derivative Solutions. Over time, I held many roles at FactSet, including programming our option pricing model and mortgage backed security analytics as a Financial Engineer, eventually leading to the fixed 79

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income Financial Engineering Team. In my last role as Vice President, I was the global head of product development for risk and fixed income analytics, leading a team of 40-45 developers globally, responsible for the development, integration, maintenance and support of a variety of third-party risk models as well as our proprietary industry-leading risk models and Fixed Income and Derivatives analytics, models, and calculation. Currently, I am Director of Strategy for Fixed Income Analytics at FactSet. In this role I am the authority on the direction of the product suite and workflow, defining the future of products and solutions through a clear product vision and road map, transparent prioritization of work and a concise go-to-market plan. I collaborate across the organization with Sales, Support, Product Development, Engineering, Research, and Marketing on an on-going basis to effectively manage the business, drive product development and innovation, and create a powerful brand within our industry. I also represent our analytics business in industry, creating space for the products I spent over a decade engineering. In this leadership role, I enjoy translating the cross-section of mathematical and financial skills into products that meet investor workflows, taking a holistic perspective considering the challenges and needs of the investment community, focusing on the future while driving the existing business. My career trajectory reflects the evolving skill sets required as you advance through your career. In the early phases, technical skills take precedence, hence sharpening and expanding technical abilities is imperative. In my field, a strong understanding of financial modeling, statistics and programming is key. Mathematics is a technical field, but as you become an industry practitioner, having intuition is imperative. I advise cultivating a thorough understanding of modeling practices and techniques, not just the formulas, but the limitations, assumptions and weaknesses. As you progress through your career, other skills such as communication, management and courageous, decisive, and influential leadership serve to continue your advancement. I enjoy having the opportunity to join both the technical and leadership dimensions in one career. In closing, I strongly encourage you to find your passion by exploring many avenues. Don’t limit your career options, a fulfilling career utilizing mathematics is lurking in every industry!

Amanda (Quiring) Gonzales

Assistant Professor of Accounting University of Nebraska–Lincoln Hastings College BA Professional Accounting and Mathematics University of Nebraska–Lincoln Master of Professional Accountancy Duke University PhD Business Administration (Accounting)

“Oh, so you’re both good with numbers!” I’m an accounting professor and my husband is a math professor and I can’t tell you how many times we’ve heard that statement. The comment considerably understates the nature, diversity, and complexity of both accounting and mathematics. Yet, the sentiment behind the comment is true in the sense that the underlying skill set that I developed in my math degree has been extremely useful as I have pursued a career in accounting. Prior to becoming a professor, I was a project manager at the International Accounting Standards Board. I spent the majority of my time researching complex accounting issues and writing papers with my related analyses and proposed solutions. Without even realizing it, I found myself applying the same approach to my work as I would to a mathematical proof – laying out all of the known relevant information, fitting it together in a logical order, and ending up with an understandable solution to a complex problem. My mathematical background also gave me a great foundation as I transitioned into academic research in accounting. During my PhD studies, I took courses in microeconomics, econometrics, game theory, and statistics that assumed an underlying knowledge of calculus, analysis, matrix algebra, logic, and methods of proof. I was so thankful that I just needed to refresh those topics, rather than start from scratch! As I pursue my own research projects now, I continually utilize the rigor of thinking that I began developing as a math student. I would highly recommend a math degree (or a double-major in math and another field) to anyone who is considering a career that requires problem-solving and logic skills. I came really close to not majoring in math. In fact, in my first 81

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week of college, I was so convinced that I wasn’t going to pursue a math degree that I dropped out of Calculus III. However, thanks to the persistence of one of my math professors, I signed up for the course again the next year and the rest is history. Even though it was extremely challenging and I had to take summer classes in order to graduate in four years, it is a decision that I have never regretted.

Amanda Hanford

Assistant Research Professor in Acoustics Head, Structural Acoustics Department The Applied Research Laboratory The Pennsylvania State University The University of Rochester BA Mathematics, Music Minor The Pennsylvania State University MS Acoustics PhD Acoustics

In seventh grade, one of our class projects was to write a biography called, “The Celebration of Me,” where we discussed our families, our hobbies and hopes and dreams for the future. I had an interesting combination of interests including playing an instrument, anything about space, and mathematics. When discussing my future plans, I said in this report, “I really enjoy music and math. It would be great if I could get a job doing both.” And so began the journey of becoming an acoustician: someone who studies the physics and engineering of sound. I always enjoyed math in school and found myself very comfortable with the logic, the critical thinking, and the universality of mathematical descriptions of our physical world. In my partial differential equations class as an undergraduate, I learned the tools for solving systems of equations with applications in acoustics. All this time I was also heavily involved with many musical activities: orchestra, classes in music theory and history, and lessons. As an undergraduate, I also attended a summer Research Experience for Undergraduates (REU) in mathematics which was an eye-opening experience for me and sealed the deal for me to continue my education in graduate school. After getting my bachelor’s degree in mathematics with a minor in music, I started graduate school in Acoustics at the Pennsylvania State University. Penn State’s graduate program in Acoustics is one of the only places in the United States where you get a degree in Acoustics that’s not part of another academic program. I went on to get both my Master’s degree and my PhD in Acoustics from Penn State. Mathematics plays a very large role in many engineering disciplines, and I found it equally exciting to build the knowledge of how to derive the constitutive 83

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governing equations and to learn how to solve them. As it is in engineering, solving governing equations can happen analytically, computationally, and/or by making assumptions depending on the application. Penn State’s excellence in Acoustics comes from its historical connection with the Applied Research Laboratory (ARL). ARL is an integral part of Penn State and serves as a university center of excellence in defense science and technologies, with a focus on naval missions and related areas. Through ARL’s connection with the University, part of ARL’s mission is also to contribute to the education, research and service mission of Penn State, while maintaining a strategic relationship with the Department of Defense and other industry sponsors. Penn State’s Acoustics department was born out of ARL’s need for acoustics expertise, and so as I finished my graduate studies in Acoustics, it was very natural that I got a job at ARL. Such a research laboratory environment provides a nice combination of defense research and technology and university related activities. Typical work consists of defense sponsored research and development. My role at ARL consists of a combination of management activities and technical work, where, depending on the project, I can work as a project manager leading a small team, a technical point of contact on larger projects, or individually. The work environment is very interdisciplinary and collaborative because we rely on each other’s expertise to meet the needs of our sponsors. As part of my appointment with ARL, I am also a member of Penn State’s graduate faculty, so I participate in many academic faculty activities such as teaching classes, advising students, and publishing scientific papers. This is a nice balance of work activities, and I’m also able to balance time spent with my family. Mathematics plays a large part in what I do day-to-day. Not only do I rely on mathematical formulations of physical systems to answer research questions of interest to our sponsors, but I use mathematics to work towards more efficient, more robust solutions, using mathematics as the universal language to engage across disciplines. The critical thinking that comes from mathematics training has helped me in many areas of my life: in management, in solving technical problems, and even outside of work.

Harold Hausman

Owner and Senior Software Engineer TechAscent University of Colorado Boulder BA Mathematics

I write code and build software systems that solve other people’s business problems. My company does consulting work, directly with other companies, activating computing resources to automate and otherwise help their business. We seek out mathematical or algorithmic problems, often involving using lots of data to build models that make predictions. We specialize in artificial intelligence, machine learning, and web development. Our goal is to build software systems that learn from data and help our customers become so efficient that they can leave work early and be with their loved ones. I founded my company with two former colleagues who are also my dear friends (networking is more important than you think it is, even if you think it is really important). Immediately before starting this company, the three of us worked together at a different consultancy doing similar things. Before that, I worked at a chip design company called NVIDIA, and before that, another startup with one of my current co-founders. He and I have worked together off and on for over ten years, and the three of us together have nearly fifty years of combined professional software development experience. Right now I am working from home, so I have tremendous freedom. I start my day with Zen meditation and, three mornings a week, I visit an indoor rock climbing gym. I get an early start, so there is time for work before lunch; work is about 85% writing code, 10% talking with customers, and 5% looking for more work (contracts). For me, writing code is a satisfying way to make a living because coming up with solutions to problems requires creativity, and you never have to solve the same problem twice. I also like communicating with customers, learning about the domain of their business, and delighting them by building things beyond their imagination. I eat lunch at noon, often with my colleagues or other friends, and in the afternoon, I will work a bit more. When I am not working, I like to 85

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spend time with my friends and family, play music or video games, and read for pleasure. When I am tired, I rest, and then I do it again. I have worked at companies big and small. When I worked at NVIDIA, they had four thousand employees(!); now my current company is only three people. Regardless of the size of the company, I love collaborating; I was surprised to learn how important it is to work with others and to get them to care about your work. When I was young, I thought of mathematicians and software people as lone rogues, carving new intellectual space in an environment free from social encumbrance. I could not have been more wrong. Working in isolation is demoralizing and ineffective. Having trusted collaborators is super fun and helps to quickly unstick tricky problems. I will say, however, that I like small teams better than large ones. A small team creates opportunities for every member to have a proportionally larger impact. There is also less of a chance of coming to feel like a tiny cog in a giant machine, a feeling far too common under the conditions of late capitalism. Math comes up in my work every day. Here are some examples. If we build a model that makes a prediction, how confident are we in that prediction? Can we quantify that confidence? Can we measure, estimate, or otherwise quantify the error in predictions that model makes? Another good example is computing resources: our programs are always operating under constraints of finite processing time and storage space for data. In particular, we built a facial recognition system that processes thousands of videos every day and creates voluminous data; it is always the source of tons of fun rate-related problems: How many videos can we process in a day with our current computing resources? If we need to process twice as many videos in the same amount of time, how many more machines will we need? What are the tradeoffs of buying more machine time versus spending development time optimizing the program? Having studied math helps my work in so many ways, but by far the biggest impact has been the proficiency I have developed in reading mathematics. It sounds silly, but it is not. Studying math teaches you to quickly assimilate and implement ideas from basic resources like textbooks, but also from advanced resources like recently published academic research. Artificial intelligence is a growing and rapidly changing field; every year we take what we learn from the latest publications and apply new techniques to solving our customers’ problems. The scientific literacy that I acquired from my university studies is completely invaluable and also quite fun. Do not underestimate the math you have already learned. I have spent more time than I care to admit relearning things (especially statistics) that lovely and amazing people tried to teach me in high school. Use your time in university to learn new things, but take any opportunity you can to refresh your understanding of the fundamentals. Ratios, discrete probabilities, basic counting things like the fencepost problem and the pigeonhole principle: all super important. And branch out! Take courses in the humanities and apply yourself to them. Your experience of your career will almost certainly be defined more by with whom you work than by what you do. Our shared human experience is at the heart of every worthy problem, and every interesting and elegant solution thereto.

Ebony Hitch

Mathematics Teacher Wicomico High School Wicomico County Public Schools University of Maryland Eastern Shore BS Mathematics

I am a Mathematics Teacher at Wicomico High School. I currently teach Algebra I and Integrated Topics, a bridge course. After graduating with a Bachelor of Science in Mathematics (Non-Teaching), I took a year off to work and save money so that I could go back and obtain my Masters. I am currently in the Master of Arts and Teaching Program at the University of Maryland Eastern Shore. I started off as a substitute for Wicomico County Public Schools; within three months of substituting, I was asked to take a long-term mathematics teacher position at James M Bennett High. While I was there, I was observed by the principal and asked to take another long-term position for the next school year. I did not instantly give them an answer but was contacted by the Supervisor of Secondary Mathematics to come in for an interview for a position at Wicomico High. The day of my interview I was so nervous that when I walked in, the supervisor immediately began to talk about my experience at Bennett High to calm me down. I was asked a series of questions, and I still remember the principal and supervisor reacting to me when I said: “I am here to teach the students not just the content, but I expect all my students to gain conceptual understanding as well as strategic competence in mathematics.” In that moment the Principal told me he had no further questions and they would be in contact shortly. Within an hour I received a call saying I was hired, and they looked forward to a great year! Recently, I walked into Wicomico High as a first-year mathematics teacher. 87

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As a teacher, there is really no normal day. Teachers plan lessons daily, but the lesson can change based on students’ performance and participation. The department at Wicomico High is built upon teamwork. All mathematics teachers who teach the same content plan for the week together and provide feedback to each other. Our department is very diverse, but we are all accepting of one another and work together as one team. My mathematics background is vital for my career. I cannot just throw problems at students if I am not capable of doing them myself. Through my experiences doing research in mathematics, the PATHWAYS internship (a National Science Foundation REU at Salisbury University focused on working with K-12 students), and working with special needs students, I have been able to apply my knowledge to help all students make mathematics sensible. The big responsibility of a teacher is to prepare our future students for society. My job is not only to teach students that mathematics is important, but also to be a role model for them. I let all my students know that 9th through 12th grade determines their future. This is the time for them to be held accountable for their actions and education. ABILITY is what you’re capable of doing. MOTIVATION determines what you do. ATTITUDE determines how well you do it. - Lou Holtz

Kelly Hobson

Software Tester Internet of Things Solution SAS Institute Wofford College BA Mathematics

I am a software tester for the Internet of Things (IoT) solution at SAS Institute. SAS develops analytics software to allow customers to access, manage, analyze, report and make decisions on their data. The Internet of Things group has been growing over the last few years as the market continues to expand. Things (machines, devices, phones, sensors) are being connected to networks and the data from these things can now be collected and processed. This can range from manufacturing lines, to oil pumps on the ocean floor, to home automation, to hospitals. As a tester, I monitor and develop tests as software features are added to the product. This can range from a simple smoke test to see if connections are working to validating model output from our advanced analytics running on the devices. Prior to this position, I was an Analytical Consultant at SAS. I was fortunate to be on a wide range of customer projects which gave me experience in general data mining, text analytics, model risk management, and matrix-based modeling. I wanted to further develop my programming and testing skills, so I started looking internally for positions in SAS Research and Development. When the IoT position came up, I knew it would be a great opportunity in a very exciting field. On a typical day, I do my heads-down work in the mornings, and in the afternoons, I’ll set up meetings with other developers or testers for questions I have about test cases or about new features being worked on. My environment is a combination of solitary and collaborative. It is a nice balance because I like to be focused and do things on my own, but I also enjoy the connection and being able to see and talk to people in person. SAS has a wonderful culture, so if you ask for help or ask questions, people are willing to help. My degree in mathematics opened the door to many opportunities in analytics, applied statistics, and programming. While I was in undergrad, I had no idea what I wanted to do, but I was encouraged by great professors to keep taking math and computer science courses and to pursue internship and research opportunities. I 89

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loved courses like Differential Equations, Numerical Analysis, and Linear Algebra, where you could apply mathematical methods to real-world problems. I considered graduate school opportunities in statistics or applied mathematics, but I wanted to test the waters in the corporate world first. I use mathematics for the bread and butter of SAS products, which is advanced analytics. The modeling techniques used to analyze large amounts of data, such as linear/logistic regression, Bayesian probability, or k-means clustering are based on mathematical formulas for fitting data. Understanding how those mathematical models work gives you the background to tune the models and interpret the output. For example, I worked on a project where data was used to generate estimates of health care coverage in rural areas (where data may be missing or incomplete) using a hierarchical Bayesian framework. We had to start with the mathematical equations given to us by a research paper and convert those into matrix operations using SAS. It was one of the more “mathy” projects, and I really enjoyed working on it. I am lucky to work at a company like SAS where they encourage work-life balance. I have a 16-month-old in daycare onsite and it has been a blessing to pursue my career and know he is in a wonderful place. The best advice I could give to someone who wants my job is to be curious and pursue challenging problems. It was intimidating taking computer science classes at Wofford but learning the logic and foundations of programming made me a better mathematics student and gave me the confidence to go for other opportunities. I encourage students to pursue summer internships and research opportunities. Leverage your college career office, alumni, current students, and family friends, asking about what is out there and what skills you need to do that job. Many people are ready and willing to help; you just need to make the initial contact. My advice for being successful in your career is to always be looking for ways to improve. One of the easiest ways to improve is to learn from your coworkers or classmates and lean on them for help and advice. I also try to go out of my way to help new hires or those who reach out to me for help to pay it back.

Marylesa Howard

Senior Scientist Nevada National Security Site George Fox University BA Mathematics, Chemistry Minor The University of Montana MS Mathematics PhD Mathematics

If you asked me ten years ago, when I was finishing undergraduate, what I wanted to do with my life, I would have told you I had no idea. Even in the middle of my doctoral program, I still had no idea. So how did I come to find myself in a PhD program without a desired career path? All I knew was I wanted a career that made me feel like I was positively contributing to society and one that I enjoyed on a general day-to-day basis, and it needed to be stable enough so that I could provide for a theoretical family, regardless what life may throw at me. While I didn’t know what I wanted to do, I believed that a higher education degree would afford me these opportunities. Lucky for me, everything fell into place when my PhD advisor included me on a research project with his colleague who worked for the Nevada National Security Site (NNSS). As I approached graduation, a new mathematician position opened up, and I was hired. Everything I wanted in a career I have found in my current position as a Senior Scientist for the NNSS, a contractor to the United States Department of Energy. As part of a small mathematics group, what we each bring to the table in terms of skill is significant and important. My background in statistics greatly complements my coworker’s background in analysis. With our combined expertise, we developed a new method for solving an ill-posed linear inverse problem that computes material densities of an object in an x-ray image, or radiograph, using a statistical formulation that mimics a commonly used regularization technique. While not in academia, our group does stay involved in that world through collaborative research with universities, co-advising graduate students’ PhD theses, and hiring undergraduates and graduates for summer internships. In addition, our group regularly publishes papers and attends conferences so we stay abreast of recent advancements in our fields. A typical day has me in the office, researching mathematical techniques for finding solutions to difficult physics models, and then writing code to put my new 91

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techniques into practice. To perform real-time analysis on subcritical nuclear experiment data, I join the experimental physicists at the Test Site—that large chunk of land in the Nevada desert where the US used to detonate nuclear bombs but that has now become a large playground for physics experiments. When at the Test Site, you can find me almost one thousand feet underground, wearing my steel-toed boots and hardhat, something I never expected to do as a mathematician. I love that this aspect of my job includes a unique working environment and hands-on experience during the data collection process. I work closely with the physicists, engineers, and technicians at the NNSS and with the National Securities Laboratories who design diagnostics that collect the data. An important part of my job is participating in discussions and meetings to ensure the diagnostics and experiments are designed appropriately so that I can develop the right data analysis tools and answer the physics questions they pose. My job also allows me to travel frequently, working in partnership with the National Securities Laboratories, though, for the most part, the amount I travel is up to me. I had my first child this year, so for the first year of my daughter’s life, I plan to stay in town more often than not. Finding a balance between work and family has come easily, mostly because my supervisors and management are all family-people, too, and don’t pressure me to overwork myself with a new family in the mix. To be successful in this position, the most important qualifications we look for in new hires are the ability to communicate appropriately and effectively with diverse groups of people, excellent written and oral skills, good computer programming experience, and the ability to work both independently and as a team member. Having breadth of knowledge in mathematics is imperative, allowing us to communicate within our group, even if we are not all experts on a particular topic. In addition, we need candidates that complement our knowledge and bring new strengths to the projects on which we work. While we work in the nuclear physics world, a background in physics, chemistry, and engineering is not required, but it is an added bonus!

Rachel Insoft

Senior Analyst Quantitative Economics and Statistics Group Ernst & Young Wellesley College BA Mathematics

I am a Senior Analyst in Ernst & Young’s Quantitative Economics and Statistics group, “cleverly” abbreviated as QUEST. We work in three main areas: Economic Impact/Policy, Statistical Sampling, and Survey Methodology. I found my job through an alumna from my college who was involved in recruiting. It was nice to have an inside scoop before accepting the position because my first job right out of college wasn’t a great fit. Since we have three areas of work, every day is pretty different! It depends on what sorts of projects I am on. Today was a fairly typical day: I started with an early morning phone call with a client in London; we are working on analyzing their survey results for a cybersecurity survey we just ran for them, and we have weekly check-in calls with the client. Then I ran a two-hour computer programming training session; all our new hires just started last month, so I was tasked with teaching them HTML. I had lunch with my mentor and then worked on writing some SAS code to analyze another set of survey data. I wrapped up my day working on writing a draft of an Economics Thought Leadership piece about state fiscal stability. Our office environment is great. There are about thirty of us in QUEST and, for the most part, everyone is in the office every day. About half of the group are PhD statisticians and economists, the other half are young adults like me who graduated fairly recently. This lends itself to a very friendly and collaborative environment. We sit in cubicles but we are always getting up and chatting, asking for help/second opinions, or taking breaks together. We do a lot of our work on our own, but then have frequent meetings to check in. Everyone is pretty close-knit 93

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and not pretentious, so it’s not uncommon to see a partner asking someone at my level for help. We often organize happy hours, baseball games, BBQs, etc. after work and on weekends. My degree in math didn’t really help me find this job (since it was through my college connections) but it definitely helped me get hired! I’m now a member of our recruiting team and I see first-hand that employers hold math majors in very high regard. Even though I studied pure math in college (and did summer REUs rather than internships), my skills as a logical thinker and persistent problem solver made me a desirable candidate. My math professors at Wellesley pushed me to be a better worker, to question everything, and to think intelligently. I’d love to tell you that I use abstract algebra or real analysis in my job, but sadly I do not (although I’m not so sad about the lack of real analysis). The core of my job is data analysis, which means collecting, cleaning, and working with a variety of data sets. I spend a lot of my day looking at figures and numbers and asking myself, “Does this make sense? Where does this come from?” Much like writing a proof, I need to take steps in a logical manner to use the data I have. My advice to math students is to never underestimate your degree and to study what you enjoy! I thought my pure math skills and experience would make it really difficult to get a job and I stressed a lot about whether I needed to take more “applied” math classes to be employable. I stuck with what I knew I would love (looking at you, Galois Theory!) and it still worked out very well. If you love stats classes, awesome! But don’t feel obligated to take something just to put it on your resume.

Eleisha Jackson

Data Scientist Livongo University of Arizona BS Mathematics University of Texas at Austin PhD Ecology, Evolution and Behavior

Growing up I always had an interest in science and mathematics. Mathematics was fun because it gave me the opportunity to solve problems. I could take a problem posed to me in words and formulate a series of equations that represented the problem in symbols. Throughout high school my love of mathematics grew. I took calculus for the first time in my junior year. After taking that course, I decided that I would study mathematics in college. This is the path that led me to study mathematics at the University of Arizona. During the summer after my sophomore year, I was contacted by a professor in the Ecology and Evolutionary Biology department at UA because my mathematics advisor had mentioned my interest in research to her. After speaking with her about the research in her lab, I decided to get involved. Over the course of the next two years I applied my skills in mathematics and programming to the field of computational biology where I studied protein evolution (i.e., how proteins change over time). After I graduated from the University of Arizona with a degree in mathematics alongside minors in biology and art history, I went to the University of Texas at Austin to study the evolution of proteins using computational methods. As I went through my studies I discovered that more than the field of biology, I was interested in using mathematics and programming to solve important problems. This led me to move to the Bay Area and start my career as an industry data scientist after graduation. After a short data science fellowship in the Bay Area, I began working at my current company, Livongo. As a data scientist for growth at Livongo I use data to help our company enroll more members and help more people with chronic illnesses. Part of my job includes helping members of the marketing team make data-informed decisions and using statistics to determine whether the results of our marketing experiments 95

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are significant. In marketing you often make changes to emails that you send to current or prospective users of your product or service. When you make a change, you want to measure whether or not the change was successful and resulted in more people converting (for example, visiting your website to purchase or sign up for your product). Statistics can be used to help determine whether or not a change (positive or negative) was significant enough to support investing in making the change you made final or keeping the old email. Assessing the results of these marketing experiments is one aspect of my job. My education in mathematics and my ability to program have been critical to my success in this industry. Those skills along with a strong sense of curiosity and an ability to communicate with people of different backgrounds are essential for being a data scientist. My degree in mathematics gave me the foundation in statistics that I use daily and helped me develop the ability to critically think about a problem. As someone who enjoys both solitary work and collaborative work, being a data scientist is very fulfilling. There are days when I spend a lot of time coding by myself and others when I have a lot of meetings with people in product, engineering and marketing to push a business objective forward. There is a lot of variation day to day in my job. In my current role, I have a good work life balance. I think part of this is finding a good company that allows people to have this balance. There are a lot of companies that fit this description. You just have to find them. For those looking to become a data scientist, I suggest continuing to learn and explore opportunities outside of the classroom as well. My internships and fellowships over the course of my studies helped me not only learn new skills and gain experience, but they also gave me insight into my own interests.

RDML (Ret) “CJ” Jaynes

Rear Admiral (retired) United States Navy Executive Technical Advisor Raytheon Company Indiana University of Pennsylvania BS Mathematics MS Mathematics Norwich University MBA

When I was a little girl, I wanted to be a veterinarian, but when my dog died and I realized that the vet couldn’t save her life, I changed my mind. Math was always my favorite subject and it came easy for me, so pursuing a degree in mathematics seemed obvious. I initially decided to become a teacher, and taught for four years at Indiana Area Junior High School. I also earned my Masters in Math during that time while attending night school and summer classes. However, I quickly became bored with teaching and decided to try something different. With no real career choice in mind, I joined the Navy to stall for four years until I could decide what I wanted to do with my life. I completed Officer Candidate School in Newport, RI and was commissioned an Ensign in March 1983. My first duty station was VT 86 in Pensacola, FL. I applied for the Aerospace Maintenance Officer program and was fortunate to be selected, thanks to my degrees in math. Aerospace maintenance is a technical field, and math majors are able to compete and succeed against engineers and science majors. I completed 33 years, retired as a Rear Admiral, and enjoyed tours in operational squadrons, intermediate maintenance activities, engineering units, and headquarters. I have been stationed in places that I would never have dreamed of seeing. Look for Diego Garcia on the globe (in the middle of the Indian Ocean) and you will see what I mean. Unbelievable! I’ve also been stationed in Jacksonville, FL; Los Angeles, CA; Lemoore, CA; Sicily; Spain; the Azores; Bermuda; Puerto Rico; Greenland; and Japan. I physically worked on A-4, T-39, F-14, F/A-18, P-3, and H-60 aircraft over the course of my career. I also had the opportunity to earn 97

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a Master’s-level degree from the Naval War College in 1995, and a Systems Engineering Certification from California Institute of Technology in 1999. I completed my MBA from Norwich University in 2008 to round out my education. I last served as Program Executive Officer for Air Anti-Submarine Warfare, Assault and Special Mission Programs (PEO(A)), had oversight responsibility for ten program offices and seven ACAT I major acquisition programs. I was featured in Profiles in Diversity Journal, 2013 Women Worth Watching, and selected for the 2017 Distinguished Alumni Award for Indiana University of Pennsylvania. I am a member of Women in Defense, Women in Aviation International, US Naval Institute, and Association of Naval Aviation. I also serve as a member of Indiana University of Pennsylvania’s College of Natural Sciences and Mathematics Dean’s Advancement Council serving as an advisor to the Dean and ambassador for the college. I currently work for Raytheon as an Executive Technical Advisor for Precision Landing Systems under Intelligence, Information and Services.

Maribeth Johnson

Boost Consultant Epic Systems Corporation Hamilton College BA Mathematics and Neuroscience

When I graduated from college, I cast a wide net in my job search. Knowing that math was my strength, I looked for companies and positions that valued mathematical skills. This brought me to the technical problem solving, or technical services, position at Epic. Epic is a healthcare software company. Our customers are hospitals and healthcare systems, and our users are doctors, nurses, billers, and other individuals who work within the health system. In the technical services position, I worked individually with a few of our customers as their main point person for the piece of the software on which I specialized. I helped my customers with whatever they needed within my area of the software. I had counterparts at the organization who I worked with closely. I’d help them with everything from setting up new functionality, to troubleshooting weird behavior they found. A typical week consisted of calls with my customers, doing research and troubleshooting for my customers’ needs, and working with other folks on my team on a variety of projects. I worked with some of the same customers for almost four years, and during that time I developed close working relationships with them. I got to know what they liked and what they struggled with, so I could focus my efforts on what would help them be successful. I went onsite periodically, and we were always excited to see one another face-to-face. After a couple years, I also became the Technical Coordinator for one of my customers. I got to work with the technical leadership at the organization as the point person for their entire Epic project. 99

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Outside of working with customers, there were endless opportunities to get involved in different projects and areas so I could specialize or branch out, depending on my interests. In mentoring roles, I helped new hires get acclimated to the position and hone their customer service and technical skills. I had opportunities to participate in all stages of development, from design to actual coding to testing. I helped to recruit at career fairs and facilitated interviews over the phone and onsite. I also spent a year leading and developing a group of experts who served as a resource for other folks on our team for a certain piece of functionality. After four years in the technical services position, I transitioned to my current position as a Boost Consultant. This position offers me more flexibility, particularly in where I live. While in the technical services position, I had to live in the vicinity of Epic’s headquarters in Verona, WI, and be in the office every day. Now, I work remotely from home, or travel onsite to the organization with which I’m working. As a Boost Consultant, I still get to work with our customers, but now in an even more dedicated way. I work with one customer at a time, devoting all of my time to that customer for a period, before moving on to another contract. I lean on the expertise I developed in my previous position to help the customer in a variety of areas (depending on the contract). Currently, I’m helping a customer that is upgrading from a previous version of our software to our most recent version. Partnering with the project team employed by the customer, I’m helping them review new features and options, making operational decisions as to how to use different new pieces of functionality, as well as building those features and testing them. I consider myself lucky finding my position at Epic right out of college. Even though what I did day-to-day required knowledge of the healthcare industry, as well as proficiency in programming, I wasn’t required to have these skills before starting at Epic. I learned a lot through training, as well as through working with mentors and exploring things on my own. Even with no experience in programming, my background in math gave me the logic skills to quickly pick it up. Coming from a liberal arts school, communication skills were a cornerstone of my education, and that mix of math and communication was perfect for my position.

Marina Johnson

Analyst Morgan Stanley Harvey Mudd College BS Mathematics

I work for Morgan Stanley in the Fixed Income Division, which is part of the bank’s Sales and Trading organization. I am what Morgan Stanley calls a desk strategist (or “strat”) and what many other banks call a quantitative analyst (or “quant”). Our job is to assist the trading desk through the creation of mathematical models and tools that, among other things, help the traders to price trades and understand their risk. I work on the Rates desk in London which means that my team covers the European Government Bond trading desk. More specifically, my team runs an automated market-making system. A market maker is a bank that provides prices for both sides (buy and sell) of trades so clients, such as investment funds, can easily find a party to trade with, instead of having to find another fund that wants to do the opposite trade. In this sense, the market maker acts as a middle man between different clients that want to do opposite trades. This means that the bank takes on the risk that they will not be able to find a client who wants to do the opposite side of the trade. An automated market-making system means that when a client asks us for a price for a trade using an electronic platform, our system automatically determines the price and sends the price to the client without direct trader involvement in the individual inquiry. If the trade is done, the system also automatically hedges the risk of the trade. A hedge trade is a trade that is done to reduce the risk of a specific position or set of positions. 101

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My role involves two main pieces: the first is monitoring the pricing and hedging algorithms to ensure they are working correctly, and the second is data analysis and modeling. This involves one-off requests from different teams for trading statistics or analysis as well as longer term algorithm development. A new algorithm starts with an initial analysis to determine if the idea is worth pursuing and, if so, we perform a more thorough back test using historical trading data. After the back test, the algorithm is implemented by the IT team with involvement and specifications from our team; we work closely with IT throughout the development process. When this is complete, the full pricing algorithm is run through a complete simulation environment before going live in production. One of the important parts of our jobs is balancing urgent requests with longer term projects. At the start of a normal day, the plan is usually to work on these projects as well as meet with other teams to discuss collaborative work and to discuss progress and priorities. A day rarely remains typical, however, as there are often last minute data requests or urgent issues that affect trading. The working environment is a combination of independent and collaborative. We work with several other teams including sales, trading, IT, risk, and modeling. Some smaller projects are handled independently while larger projects are discussed and planned across the team with individual pieces being completed independently. Many people might assume that working in a bank means that you will spend all of your time in the office and have no social life. This is certainly not the case. Working in banking does mean that the working hours are typically longer than many other jobs, but does not mean that you will spend all of your time at work. As with any job, the hours you work are largely dependent on your time management and the workload of the team at any given time. In the two years I have been at Morgan Stanley, I have had weeks where I have had to stay late every evening, but I have never had to work or go into the office on the weekend. I think that working for a bank offers a unique challenge in the finance world. The interesting challenge that you will not find at places like hedge funds is that we have to price both the trades that we want to do and the trades that we do not want to do. This means that the problem becomes one of accurately pricing all trades instead of just finding desirable trades. If you are interested in working in electronic trading or electronic trading algorithm development, the most useful areas to study are mathematics and computer science. Economics and finance courses can also be helpful, but in my opinion are not as helpful as the former. I would also strongly encourage you to consider a summer internship. This is helpful for two main reasons: first, it provides you with the opportunity to see if a career in banking is a good fit; and second, many banks use summer internships as a pipeline to their full-time campus programs.

Erin Jones

Go-To-Market and Sales Strategy Manager RSA, The Security Division of Dell Technologies Carleton College BA Mathematics

As a first generation college student I was unaware of the challenges that faced me when pursuing my mathematics degree at Carleton College. Being a studentathlete playing varsity football and collegiate rugby put an immense amount of pressure on me to not only succeed in the classroom, but also on the pitch. But even with those hurdles in front of me, I knew deep down that I had to pursue a degree that challenged my work ethic, my perseverance, and my mind. I was never a role model student by any means, but my professors and peers knew that once I set my mind to accomplishing something I was not going to pursue it lightly. Following graduation, after an internship year with Dell Technologies (formerly EMC) I was granted a full-time position as a corporate financial analyst. I only knew about finance through my three courses of economics I took at Carleton, so I knew I would be up for yet another challenge. Being an athlete made me always want to be better and do better, so each year I continued to press forward in my pursuit of what I then thought was my career in finance. Two years later, I met my wife, a Perioperative Registered Nurse, and another chapter began. What she and I both knew was that I had a natural ability to consume large amounts of information, analyze it, and provide constructive conclusions to help us both in our professional and personal lives. I found myself with an opportunity to pursue a career in Sales Operations within EMC, and later RSA, that would change my life forever. Most analysts only think of their day job as “data miners,” where 103

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I thought of it as an opportunity to expand my knowledge into understanding the inner-processes that make a company successful. For example, if I was given a dataset which had our gross revenue trends and annual operating expenses, I used my math skills to break those trends and expenses down into “operating/business actions.” I then used the knowledge I’d gained in corporate over the years to determine whether any of these actions need to be addressed in order to improve performance in sales productivity. Four years from that point, I am now a manager supporting an $850+ million dollar company leading strategies that make each of our four business units successful. Throughout those four years I took many management and leadership development courses that helped me round out my technical skills with my soft skills learning how to manage people as well as projects. Those courses made my career take a whole new turn because now I knew how to influence my peers and executive staff to trust my abilities, analysis, and leadership; which would later steer them into offering me my current position. A normal day now consists of many calls and meetings with senior leaders within the company discussing how we can best maneuver the company into the next level of success within our sales organization. The same way I worked my way into a degree in mathematics, I also found my way into my career by never allowing myself to be complacent with the knowledge I had obtained. Mathematics did not just teach me how to work with numbers in a skillful, dutiful way, it also taught me to never give up! With all these things I have experienced, the joy I get from my personal life far exceeds any that I receive helping my business succeed. Since graduation, I have been a sponsored obstacle course runner, I’ve completed multiple half and full marathons including one ultra-marathon of 60+ miles, I’ve competed in bodybuilding competitions, I have been an active yoga instructor for almost four years, and I continue to challenge my soft skills within my marriage. As math has surely taught me, it is not about the solution to the problem, but the journey that gets you there. You’ll never be truly satisfied just having answers without understanding the process. Trust the process, believe in yourself and always remember to have faith.

Barbara Jordan

Assistant Vice President Credit Risk Management GM Financial Sam Houston State University BS Mathematics

The phone rang. I was needed to immediately come down to speak to a room full of four- and five-star generals. They were in full uniform. I was barefoot, in yoga pants and a bright red t-shirt emblazoned with the words “hot stuff.” Not only that, I was only twenty-one at the time. Such were the days early in my mathematics career. Currently I’m an Assistant Vice President in the Risk Management Department at GM Financial, the lending arm of General Motors. My team and I make up the Lease Forecasting group, which forecasts default losses on our lease portfolio. This group – merely myself and three others – was created after moving me over from the Decision Analytics group, also in the Risk Management Department, and promoting me to Assistant Vice President. Because the group is brand new, work is never boring. The lease history is newer as well so there’s little to work from. We’re constantly digging into the data to further our understanding of the intricacies of leasing, and we find more surprises as we go. Creativity with forecasting methodologies is a must. For example, we thought we could work with a methodology similar to the loan forecasting team, but ended up scrapping almost everything and developing the model from scratch because loans and leases are not alike. However, this makes my job very interesting! It is never the same from one day to the next for me and my team. If there is anything consistent in my day-to-day work, it’s communication. In my specific role, I work with not only my team, but frequently with others as well. I communicate with my team to ensure that they have what they need while also making sure I have a handle on everything going on. I communicate with my 105

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management so they’re fully informed. I also collaborate with other managers to give information, or to ask questions and receive insight to make sure I have all the information necessary for the most accurate forecasts. Since I really enjoy meeting and talking with people, I especially love this aspect of my job. My advice to others is to be open to opportunities. It can be scary, but you can learn so much doing that! I am a big believer that the more knowledge you have, the better you can be at your job. It doesn’t even have to be directly relatable knowledge to help. Don’t feel like once you start in an industry or type of job that you are stuck there. Along my career path, I’ve worked for the National Security Agency, Lockheed, and in the oil and gas Industry, before shifting to the automotive industry. While I’ve worked in different industries, I am still analyzing data. Mathematical knowledge can be applied anywhere. You only need to learn the industry specifics to transition smoothly. Develop contacts and make friends wherever you go. You never know when those contacts will come in handy! I started working at GM Financial because a friend who worked for them thought I’d be a great fit in their Risk Department. I decided to interview for the job since if I got the job, I could walk to work. During the interview I realized that I really would be a good fit, so I accepted their offer. That was in 2011, and I’ve been there ever since. Data tells a story. What is it saying? What do the results mean? Does it make sense? If not, what questions do I need to ask? What questions will others ask? In the end, I am digging through data to see what it wants to tell me, and that’s what I love about everything I’ve ever done so far. Even if I’m no longer running meetings while wearing a t-shirt that says, “hot stuff.”

Harlan Kadish

Field Software Engineer Tamr Inc. California Institute of Technology BS Mathematics University of Michigan PhD Mathematics

Studying mathematics isn’t the only way to learn how to solve problems, or even how to solve technical problems. It’s not the only way to learn how to research independently, or how to explain complicated ideas to a variety of audiences. But mathematics was the right way for me to learn those things, and, six years out of academia, it’s still serving me well. As a field engineer for the machine learning software startup Tamr, it’s my job to make the customer successful with our product, which does complicated things and evolves rapidly. Our customers are biotech firms, international manufacturers, national security agencies, and even cruise ship operators. They care about finding the analysis of a certain chemical, what sorts of things they spend the most money on, how to catch drug smugglers and terrorists, or which ships have spare turbine parts (respectively). To achieve those goals with machine learning tools, I care about details on a different level: decision trees, binning functions, parallel processing, clustering algorithms (in no particular order). It’s my job to use those tools, summarize their contributions, and deliver the results. All the while, my company’s software is developing new features, new bugs, and new subtleties. I communicate back to our development team how those changes affect the customer, so that we can better meet the customer’s needs. This role is not unique to fast-moving startups: my previous employer, five times as large, had provided data transformation solutions for twenty years. I performed similar work for them under the title “internal consultant.” I chose to study mathematics because I love applying structure and logic to learn or discover new things. Similarly, by writing efficient data pipeline code and tuning our machine learning algorithms carefully, I reveal new insights and patterns in our customers’ endless, murky swamps of data. Depending on the stage of a project, I may have lots of meetings one week, or I may be installing new systems 107

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on new servers, or I may be writing code. I learned how to configure and monitor enterprise servers on-the-job, but my customer relationships and programming skills stem directly from my mathematics courses and research. Studying mathematics taught me to think precisely and communicate clearly. Programming requires the same sort of precise thinking as studying mathematics: a computer does exactly what you tell it to do. If you want a computer to do a complicated task, you have to tell it how, every step. Fortunately, as in mathematics, you can use abstraction to repeat that task in a variety of circumstances, without having to revisit all the steps. Finally, because I’m working in the “field,” I present my results to the customer. Like giving a seminar talk or writing a paper, I choose the right level of detail for the audience. I gauge their reaction and check for understanding. I develop consistent terminology and supply examples. Sometimes, only a diagram can convey the message. Working in industry gives me more control over where I can live and how long I can stay there. The transition from pure mathematics to software engineering is becoming easier as modern mathematics makes more use of technology to explore examples and test hypotheses. Even better, writing programs in mathematicsoriented languages like Mathematica or Maple provides an excellent introduction both to mathematics research and to high-performance programming. This computational work can lead not only to new mathematical knowledge, but to a variety of career opportunities.

David Keyes

Senior Program Manager IXL Learning University of California, Berkeley BA Mathematics and History The University of Colorado Boulder PhD Mathematics

For me, there is nothing more rewarding than teaching. As an undergraduate, I worked in the campus tutoring center. As a graduate student, I got to play professor and teach my own sections at CU Boulder. I always requested teaching assignments for topics I hadn’t yet taught before, as I enjoyed writing lesson plans from scratch each semester. Post graduation, I wanted to find a job that allowed me to continue teaching and help others learn, though I wasn’t sure exactly what form that would take. While there are certainly a lot of teaching opportunities for those who study math, until recently most were focused on either the traditional K-12 classroom or academia. I knew I did not want to manage the unique challenges of being in the K-12 classroom, and I also did not want to continue doing academic research. Luckily, the field of educational technology was growing and I was able to land a job at IXL Learning, an online math learning solution for K-12 students. While teaching is my core responsibility at IXL, my role has evolved a lot since I started in 2011. Initially I was a curriculum designer and wrote the questions and explanations for our math skills along with one other teammate. My primary responsibility was teaching math to students at scale through online practice. As the company grew and my team expanded (we are now 30 strong), the type of teaching my job requires has changed. In addition to teaching math students around the country who use our product, I am also responsible for teaching and coaching my own team at IXL to grow professionally so that we can collectively meet our project goals. Since my team is half remote and spread out across 10 states, this type of 109

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teaching and coaching comes with its own unique set of complex (but rewarding!) challenges. Studying math has helped me in other ways too. Most notably, math trains you to break down large complex systems into understandable, bite-sized, and welldefined pieces. The project we are currently working on is a multi-year project with many moving parts and dependencies. Scheduling for this project was made significantly easier by approaching the problem mathematically as well as having a team of mathematicians to help me solve it! Something I would like to impart to those studying math and looking for private sector jobs is that being able to communicate your ideas clearly and work with others is of the utmost importance. There are a lot of brilliant mathematical and technical minds out there, but not enough of them are strong communicators. Being able to have both – the mathematical problem solving abilities and communication skills – will allow you to go far. And as my final plug, there is no better way to practice these communication skills than teaching.

Stacey Faulkenberg Larsen

Lead Analyst Business Intelligence and Analytics Target Corporation Bellarmine University BA Mathematics Clemson University MS Mathematical Sciences PhD Mathematical Sciences

I was drawn to math from a young age, so I was never undecided about what I wanted to study in college. The question for me was what I would do with a mathematics degree. From my limited perspective, I felt that I only had two options: teach or become an actuary. I knew I wasn’t cut out for teaching and the business context of actuarial work didn’t necessarily feel like the best fit for my interests either. Regardless of these hurdles, I pressed on with my mathematical studies, pushing any thoughts of my long-term job prospects out of my mind. In my junior year, I took a course called “Introduction to Operations Research.” At the time, I didn’t know what Operations Research (OR) was, so it was a bit of a daunting experience. But my leap of faith was worth it: that class opened my eyes to a whole new family of careers in math. It was truly my “Aha!” moment. The moral of the story is: don’t be afraid to take courses or learn things that may seem outside of your comfort zone! After college, I moved on to grad school to specialize in optimization, which is at the heart of OR. As I was finishing my dissertation, I learned about an opening at Target for an Optimization Analyst role. I had never considered a career in retail (at the time, business analytics was in its infancy), but the problems they were solving sounded fascinating, and who doesn’t love Target? My role at Target has evolved and changed over the years in terms of both business areas and the types of math and analytical tools that I used. I started 111

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my career on a team which was building a large-scale optimization tool for recommending optimal use of space in the stores: for example, we made recommendations around which shelf an item should be on and how many times the item should appear on that shelf. From there, I switched focus to inventory and supply chain where I typically juggled several projects at once, ranging from quick data pulls and reports to longer-term projects investigating questions like “Why are we always out of stock in a certain product?” or “What sort of opportunity exists to reduce inventory in low-volume stores?” After that, I did a quick stint on the Target.com team, focusing on gift registry, before I came back full-circle to my current role again: supporting space in the stores. As you can tell, one of the benefits of working for a large company like Target is career flexibility. If I become bored in a role, I can switch to a different area of the company with new data to explore and new questions to answer. And in a retail company like Target, we have data on everything! My career has only touched a few areas, but there are many others that use analytics: Human Resources, Property Development, Pricing, and Finance, just to name a few. Day-to-day work in an analytics position at Target is very collaborative, and continued learning and knowledge sharing are highly encouraged. We have people from a variety of different backgrounds on our team (math, computer science, engineering, psychology, etc.). What connects all of us is a love of solving problems using data. From my perspective, the key skills needed for a career in retail analytics are critical thinking and curiosity, some sort of background in math, the ability to pull and manipulate data (a basic understanding of computer science helps here), and being able to synthesize and explain analytical results to business-focused decision makers. The latter skill, and communication skills in general, are often overlooked by students majoring in technical fields in college, but are extremely important. If you have these qualifications, then a career in this field could be for you. My favorite thing about my job? I get to exercise mathematical creativity in my approaches to solving the problems presented to me. Having an ownership of the methodology used in a solution brings great satisfaction.

Dan Loeb

Quantitative Research Analyst Susquehanna International Group California Institute of Technology BS Mathematics Massachusetts Institute of Technology PhD Mathematics

Ever since high school, when I attended the Hampshire College Summer Studies in Mathematics, I planned a career in mathematics. At first, my career took a traditional academic route: I earned a Bachelors of Science Degree in Mathematics from Caltech. Professor Richard Wilson introduced me to discrete mathematics which would eventually become my thesis topic at MIT. Meanwhile I added breadth to my mathematical training by taking a number of computer science and economics classes. Caltech teaches microeconomics and game theory from a very mathematical approach. In fact, I often found the mathematics in my economics courses more challenging than the mathematics in my math courses: maximizing a function of a dozen variables with several constraints, whereas in math after getting past explicit examples in two or three variables we always went straight to the “general case.” At MIT, I studied umbral calculus (a branch of combinatorics) under the direction of Professor Gian-Carlo Rota and received my PhD in 1989. I then taught and continued my research at the University of Bordeaux in France. In 1996, I was looking to take a sabbatical and return for a while to the United States. A coauthor of mine, Walter Stromquist, encouraged me to consider nonacademic employment, so I applied to Daniel H. Wagner Associates, where he was in charge of their Pennsylvania office. My first projects at Wagner Associates were redesigning the corporate website (which was a great initial project since it exposed me to the wide variety of mathematical work done at the firm) and the evaluation of a credit risk model used by BMW based on fuzzy logic. 113

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However, I soon started working in mathematical finance for the Susquehanna International Group for their newly created Statistical Arbitrage Group in their Quantitative Research Department. As this project continued to be successful and grew in size, it took up all of my time, and I eventually left Wagner Associates to work full time at Susquehanna where I am now responsible for a group of over a half-dozen mathematicians developing proprietary trading strategies with which to invest the partners’ money. Having worked in both industry and academia, I appreciate the camaraderie of working within a group of mathematicians like I have at Susquehanna, similar to that at most universities. We share the same mathematical sense of humor and enjoy puzzles. Outside of Quantitative Research, there are many traders who have ideas for us to try and who would like to exploit our models. However, traders will typically give a few examples rather than express their ideas as a mathematical equation to be tested. Part of the excitement of my work is translating the ideas of the traders into mathematical formulae, and conversely helping the traders better understand and visualize the mathematical concepts behind our trading models. In academia, I spent most of my time working on publications. In many cases, years would pass between writing up an idea and actually seeing it in print. At that point, I felt I was wasting my time encouraging people to read my specialized work. For example, the paper I am perhaps proudest of (Invariant Umbral Calculus) requires a strong background in combinatorics, Hilbert spaces, and umbral calculus and physics; it is not surprising that articles like that get limited readership. On the other hand, at Susquehanna, almost all of our work is confidential, so I do not publish anything except in my spare time. However, my work is exciting, and if I find something useful, I know it will get applied quickly. In some cases, it was literally minutes between coming up with an idea, implementing it in one of our computer-based strategies, and actually trading it on the New York Stock Exchange. Recently, I have become very involved in the mathematics of redistricting, including working with legislative teams and in giving expert testimony in court cases regarding gerrymandering.

Aaron Luttman Principal Scientist Nevada National Security Site Bethany Lutheran College AA Liberal Arts Purdue University BS Mathematics University of Minnesota MS Mathematics University of Montana PhD Mathematics National security is not just a topic of political conversation. It’s an actual industry with thousands of people, and there are tremendous opportunities for mathematicians to contribute by solving challenging mathematical problems and by helping to direct our national security posture. One component of US national security, with far-reaching policy impacts, is the science-based Stockpile Stewardship Program, whose focus is the science and engineering of nuclear weapons without supercritical nuclear testing. The Stockpile Stewardship Program, which is overseen by the US Department of Energy’s National Nuclear Security Administration (NNSA), is comprised of large-scale, explosives-driven experiments and the algorithms development and computer programming to model and simulate the associated physics. Mathematicians play important roles in this enterprise through algorithms development, numerical analysis, and data analysis, but also in helping to drive the policies and scientific directions of the entire nuclear security enterprise. My mathematical background was in both pure and applied mathematics, so, when I got my PhD, I became a university professor because that was the common thing to do. After a few very enjoyable years of teaching and academic research, though, I decided that I wanted to use my mathematical skills in different ways. That led me to the Nevada National Security Site (NNSS), which is a research laboratory complex larger than the state of Rhode Island, out in the middle of the Nevada desert. We perform a wide variety of scientific experiments at the NNSS, ranging from above-ground chemical explosives testing to underground hydrodynamic studies of nuclear weapons materials to the design and development of nuclear fusion reactors. The purpose of all experiments is to obtain information, which is usually inferred indirectly from measured data, and our group of mathematicians models the measurement systems, called diagnostics, to maximize the 115

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value of the information that can be extracted from the data. When your experiments cost $65 million dollars and take five years to complete, it’s important to learn everything possible from every measurement! There is no such thing as an “ordinary” day for me. Some days, I work out of an office in North Las Vegas, where I have six very large white boards for debating mathematics with my colleagues. When I’m in the office, I also host a lot of meetings, since a group of about 25 scientists, engineers, and mathematicians reports to me. Other days I work 1000 feet underground, wearing a hard hat and safety glasses, overseeing experimental preparations and installation of diagnostics. I also travel frequently, attending meetings and research collaborations around the country, including several research programs we have in partnership with universities. Beyond scientific work, there are also tremendous opportunities to influence nuclear policy. The Stockpile Stewardship Program is directed from Washington D.C., and my experiences with the experimental program prepared me to represent Nevada in the Office of Research & Development at NNSA headquarters. During my time there I did essentially no mathematics, but I was able to have a day-to-day impact on how the NNSA directs nuclear weapons science. The work there is not mathematical at all, but it was, nonetheless, my mathematics training that best prepared me for program-level thinking. I have a pretty extreme personal bias on what mathematics courses are the most important, but I firmly believe that any applied mathematician must have a very strong background in real analysis. Linear algebra, statistics, and some form of computer programming are also important. On top of taking mathematics courses, the best trainings for work in the NNSA are internships or undergraduate research experiences. In our group we only hire PhD-level mathematicians into full-time positions, but most of our full-time hires started with us as undergraduate interns. We encourage all of our interns to pursue graduate studies, and we often assist in funding their graduate work and help to develop doctoral research projects focused on problems of interest to the NNSA. The work we do is not hypothetical; the data we work with is real. Along with real data come real impacts and, with real impacts, real responsibility. When we get things wrong, it matters. When we get things right, though, we get to see tangible benefits to the country, and there will always be exciting work in the national security enterprise for mathematicians who are willing to serve.

Dana Mackenzie Freelance Writer Swarthmore College BA Mathematics Princeton University PhD Mathematics University of California, Santa Cruz Science Communication Program

As a freelance mathematics and science writer, I often tell people that my job is to get free lessons every week from the smartest people in the country. Most of my work when I was starting out consisted of articles for popular science magazines, such as Discover, New Scientist, Science, and others. Usually, I would be assigned a story by an editor; sometimes, I would generate the ideas myself. In science writing, the articles are usually about a new piece of research. My job is to interview the people who did the research and some other experts in the field to get some different perspectives on it. There’s also some reading involved, so that I can ask reasonably intelligent questions. Finally, I write an article that communicates the main points in simple and entertaining language for readers who know nothing about the field. Note the words “simple” and “entertaining”! The reason that we need science writers is that most scientists do not know how to write either simply or entertainingly. In recent years my writing has gradually moved to longer-form articles and books, which I find rewarding because they have greater permanence than magazine articles. There is also less deadline pressure! My first two books were about the origin of the moon (The Big Splat, or How Our Moon Came to Be, Wiley, 2003) and about the history of twenty-four great equations (The Universe in Zero Words, Princeton University Press, 2012). I am currently at work on a third book that straddles the boundaries between math, statistics, and artificial intelligence. I describe myself as a mathematician who went rogue. For a long time I followed a very standard academic path, teaching at Duke University (six years) and Kenyon College (seven years). But I gradually realized that it just wasn’t quite what I wanted to spend my life doing. My life and career were changed in 1996 by the World Wide Web, at that time a newfangled invention, which allowed me to learn about opportunities I had no inkling of before. I happened to find an article online 117

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about the Science Communication Program at UC Santa Cruz. I knew almost instantly that this was the path for me. I had always liked writing, and I had longed to tell people how beautiful and misunderstood mathematics is. But I hadn’t known how to do it. The SciCom program was meant for people like me. In one year, it teaches you the ropes of journalism and gives you the contacts you need to make a successful start. Writing demands an unusual combination of characteristics: you need to be gregarious but comfortable with solitude. Or vice versa, you need to be a loner who can turn on the social charm when necessary. Especially as a freelancer, you spend many hours working on your own. Yet you’re constantly interviewing strangers, so you need good social skills both on the phone and when talking in person. Writing is the perfect profession for generalists. In academia, you are forced to specialize: first you declare a major, then one field within that major, and eventually you become the world’s top expert in one narrow problem. Writing is completely the opposite. I could be writing about astronomy one week, the Higgs field the next, and group theory the week after that. It keeps my mind fresh and keeps me looking for the big picture. I’ve found that my background in mathematics is particularly advantageous because most journalists are scared of math. So if I can find a story that’s either about math or that involves math, chances are I will not have much competition. Sometimes I can take a topic that has been well-mined by other journalists (such as the Higgs particle) and come up with a fresh take on it because I can understand the underlying mathematics and they can’t. I believe the biggest roadblock that keeps students out of science writing as a career is that they don’t have any idea that it’s even a possibility. Fortunately, there are several ways to try it out. You can apply for an AAAS Mass Media Fellowship, or an internship at a science-oriented publication. (In fact, even an internship on a non-science publication, such as a newspaper, can help you establish your credibility and get some “clips.”) A formal graduate program in science writing, like the one at UC Santa Cruz, is ideal if you are ready to commit yourself to this career path. I think it’s easier to get started and to make a comfortable income as a staff writer or editor (on a publication) than a freelancer. For personal reasons, though, I really wanted to be my own boss. Finally, if you do choose to become a freelance writer, I have one more little tip: it helps to marry somebody with a regular job and health insurance!

Chad Magers

Scientist Naval Surface Warfare Center Dahlgren, VA Mississippi State University BS Mathematics MS Mathematics

I am a scientist in the research and analysis division of the Submarine Launched Ballistic Missile (SLBM) program here at the Naval Surface Warfare Center, Dahlgren Division. To do my job well, I must be able to write software tools for data analysis, model both simple and complex problems using mathematics, verify and validate data analysis tools, and understand the complex error models that we use to validate our system. To say that mathematics has provided me the tools to do my job well would be an understatement. At the Naval Surface Warfare Center, we take pride in our technical expertise, especially areas where math is the core of the discipline, e.g. physics, electrical and mechanical engineering, operations research. Areas of mathematics that we use on a daily basis are: • Multivariate Calculus • Geometry: Euclidean and spherical • Differential Equations: missile trajectory models • Numerical Analysis: schemes for solving algebraic and differential equations, matrix decompositions and Legendre functions • Linear Algebra: least-squares, rotation matrices, eigenvalues/eigenvectors • Probability: Normal, exponential, uniform, etc. density functions, expected values, conditional expectation • Control Theory: optimal and suboptimal Kalman Filtering One of my jobs is to update and analyze one of our legacy functions used to preset a missile. My mathematics background has allowed me to quickly understand what was done in the past and why. It helps tremendously in determining how we might improve the system, whether that improvement is in the algorithm itself or the documentation of the current methodology. 119

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Often an accurate model/design must be implemented in a timely manner, and the problem solving skills and tools one gains from mathematics training is of the utmost importance. Employers realize that candidates with a mathematics background can do many different things well, and they are able to learn quickly what they do not know. In short, one cannot go wrong by majoring in mathematics.

Alex McAdams

Senior Software Engineer Walt Disney Animation Studios DePauw University BA Mathematics University of California, Los Angeles PhD Applied Mathematics

As a software developer at Disney Animation, I have the opportunity to work with amazing artists to create some of the tools they use to craft our films. My particular role is as a member of our simulation technology team. As the demand for visual complexity in our animated films has grown, we’ve turned more and more to the use of physics-based simulation to create richness in our characters and the world they interact with. Today, artists use these simulations to animate the characters’ cloth and hair, as well as to do physically plausible volumetric deformation, and to add secondary motion like jiggle to their bodies. We use familiar techniques from continuum mechanics and numerical differential equations to do these simulations; however, whereas most applications of these methods are to perform physically accurate simulations that are predictive of the real world, our simulations need to perform in the invented world of our films. Therefore, while based on core physical models, our approaches need to handle non-physical inputs to produce results which are physically plausible and art-directable. It’s not enough to show how a particular hairstyle would hold up in a real windstorm; the art-directed hair might need to flutter and whip around convincingly like it’s in a windstorm, while also perfectly framing the character’s face! My job as a simulation software developer is therefore a balance of developing solvers which provide the intuitive richness of a realistic physics simulation, while also giving the artists control to bend physics to meet their artistic demands. This is a highly collaborative process, and involves working with artists to discover their needs, experimenting to determine the best solutions given the available resources, and lots of coding. Typically, when faced with a particularly challenging problem, my first step is to do a literature search of computer graphics, as well as more general existing solutions. Often, I’m able to adapt one of these solutions to my problem. However, when new research is called for, in addition to working with developers 121

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at the studio, I have the opportunity to collaborate with Disney Research scientists or other academic researchers. In all cases, I spend a lot of time doing math. My path from an undergraduate math major to Disney Animation was surprisingly direct. As an undergrad, I was encouraged to participate in a summer Research Experience for Undergraduates (REU). That summer, I worked on a computer vision project which was my first introduction to applied math and computer programming research. By the end of the summer, I wasn’t sure exactly what I wanted to do as a career, but I did know that a PhD in applied math was going to be my next step. In my first year of graduate school, I took a range of courses including one in computational fluid dynamics, and from that moment I was hooked on numerical methods for physics simulation. I’m very lucky that around that time my advisor Joey Teran joined the department, as his work in computational mechanics was a great fit. Through him, I was connected with Disney Animation’s graduate research internship program. I ended up doing two internships with Disney, and in both, I worked on research problems that resulted in research publications – one on modeling hair contact and collisions, another on using deformable solid simulation for character animation. In fact, I was excited to see the research I started as a graduate intern become a fully-fledged soft-tissue simulation tool used by artists on Zootopia. My advice for anyone looking to pursue a career in the industry would be to seek out “hands-on” opportunities like research internships. As with so many careers, a graduate degree isn’t necessary, but it’s a good way to gain knowledge and experience and to make connections. Finally, while I use math just about every day at my job, I definitely spend every day developing software, so strong programming experience, which often comes with applied math research, is essential. I feel incredibly privileged to have the opportunity to continue using math to solve both technically and creatively interesting problems while working with such a talented and diverse group of people.

Carissa Mendoza

Senior Inside Sales Representative Trace3 University of Redlands BS Mathematics

I entered my freshman year at the University of Redlands fairly certain that I would become a math teacher; at the time, I had no idea how many different career paths someone who excelled in math could pursue. After a year or so, I decided that I did not want to become a teacher, but I wasn’t sure what I’d rather be “when I grew up.” I continued my study in math and also studied Japanese language and culture to prepare for a semester abroad in Tokyo. During my time in college, I participated in an REU at CSU Channel Islands, led by Dr. Cindy Wyels, which opened my eyes to not only more potential career paths, but the joys of collaborating on a project and problem solving in a group setting. When I graduated with a BS in Mathematics and a minor in Asian Studies, it was not the best time to enter the workforce without much work experience. Due to this poor timing, I struggled to find work for almost a year. I finally applied for a temp agency and was hired for a temp position with the first company that interviewed me. I was beyond relieved that I would be able to start making payments on my student loans. I did not see myself having a career as an office assistant or otherwise in the building automation industry, but my temp job turned into a full-time position as a Service Coordinator. I used basic math on a daily basis, calculating prices on parts quotes and technicians’ work orders to be invoiced. I excelled at managing inventory and most enjoyed purchasing. After about three years in this role, I was ready to be more challenged in my work. I searched for 123

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something in a hot industry where I could start entry-level but hopefully continue to do purchasing, and eventually put my degree to use. Early in my search I found Trace3, a transformative information technology authority, and premier provider of information technology solutions. I started in purchasing as an Orders Administrator, which was a great introduction to the company and industry. While I’ve still been searching for my ideal career and the company has been growing, I’ve been able to try different positions within the company as my interests and skills have aligned with where help is needed. I enjoyed the basic accounting and attention to detail required as Trace3’s Invoicing Manager, but after a move to Los Angeles I decided it was time to give sales a try. After about a year as an Inside Sales Representative, I was promoted to Senior Inside Sales Representative. Every day my work is different. Some days I work from home and spend the day managing support renewals and creating quotes, and other days I’m brainstorming with our team of elite engineers and sales executives, collaborating on ways to protect and serve our clients’ interests. My current work requires minimal math skills, and most of my math is done via Excel, such as calculating gross profit and estimating support renewal amounts, but I often get to teach others how to do these tasks more efficiently. While my degree didn’t help me find my career, it did allow me to develop the problem solving and critical thinking skills necessary to excel in business operations. I foresee more mathematics in my future, as I consider preparing for a career in Business Analysis.

Carol Meyers

Mathematician and Project Manager Lawrence Livermore National Laboratory Pomona College BA Mathematics Massachusetts Institute of Technology PhD Operations Research

Don’t you hate it when you meet someone for the first time, and you tell them you are a math major, and the response you get back is, “oh, math! I have always hated math!” These sorts of exchanges used to make me so sad when I was in college, because I thought math was both beautiful and awesome. I resolved then that I wanted a career where I could use math to tackle interesting real-world problems, so that when people asked me about my job, they would say, “Wow, cool! You use math to do that?” I work at Lawrence Livermore National Laboratory, which is home to the world’s largest laser, frequent home to the world’s fastest supercomputer (those records don’t last long), and the namesake to element 116 (Livermorium) on the periodic table. National labs serve a role between academia and industry, solving problems too large and too applied for academia, and insufficiently profit-driven to be tackled by industry. Most of our work is funded by government agencies, and all of it is “in the national interest,” meaning we create science and technology solutions for the country’s biggest problems. Some of the areas in which I have worked include: energy grid modernization, nuclear counterterrorism, cyber security, stockpile stewardship, and supercomputing. My mathematical background is in optimization, and I am often brought in as a consultant offering mathematical modeling expertise. This usually involves working with teams of other scientists, including engineers, physicists, computer scientists, earth scientists, and statisticians, and often in collaboration with other national labs and academia. I’ve gotten to visit some pretty cool places as a result 125

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of my job, including touring a nuclear submarine, a stealth bomber, an explosives range, a B-52 aircraft, and the Pentagon. One of the projects I have led involved taking a commercial energy grid modeling software code and showing how we could run it on supercomputers to change the scale of problems that could be answered. In this case my expertise in integer programming optimization was crucial for understanding the “guts” behind the commercial code, while computer scientists on my team ported the code to work on supercomputers. We were also fortunate to have two fantastic industry partners who implemented modifications to both the commercial energy code and its underlying optimization software. Being a math major is helpful in my occupation, not just in terms of providing subject matter expertise to areas that need it, but also in terms of building models for problems that can be difficult to express quantitatively. For instance, many government policy questions cannot easily be stated in numerical terms, and our job is to figure out ways to evaluate these policies given the data that we have combined with the qualitative thoughts of experts in the field. Having a logical foundation in mathematics really helps to take these abstract ideas, make them concrete, and then find a way to assess them. In addition to the extremely diverse set of problems that I am able to work on, one of my favorite parts about working at a national lab is the priority placed on achieving a manageable work-life balance. I have two young kids (ages one and five) who attend our employer-affiliated daycare, and there is a tremendous peace of mind in that. I am also co-chair of the new moms’ group at my workplace, which has been a fantastic resource to me in terms of providing a supportive network of people who deal with many of the same issues and lobby for change when needed. Altogether, my workplace is a consistently interesting place to be, and I am happy that math has brought me here.

Erika Meza

Project Associate The RAND Corporation Loyola Marymount University BS Applied Mathematics and Spanish Mailman School of Public Health Columbia University MPH Environmental Health Sciences

As an undergraduate math major, I sought out opportunities to learn about the myriad real-world applications of mathematics. I knew I enjoyed problem solving and was fascinated by the ways math could be applied across different fields of study from computer animation in movies to the psychometrics behind SAT or ACT scoring rubric. I was certain that I wanted to apply my math degree to help solve real world problems, but I did not know how or in what field exactly. My junior year in college, I participated on a service trip to El Salvador focused on access to clean drinking water and community health. I knew that I enjoyed working in the community, interacting with people and hearing their personal accounts about their health and well-being. So after some research and discovering the existence of disciplines like epidemiology and biostatistics, I realized I wanted to apply my problem solving and critical thinking skills towards developing effective methods and practices that address health disparities and help improve community health. I completed a Masters of Public Health degree, and while I felt like an outlier in my health science classes, the quantitative courses quickly became my favorite. Every health study, whether an experimental randomized control trial or an observational cohort study, requires math and statistics to determine a crucial set of parameters (like the sample size of the treatment group) as well as the study results (the likelihood of an outcome across different groups). As a project associate at RAND, I have the opportunity to collaborate and provide support on different research studies with interdisciplinary teams that include statisticians, epidemiologists, and social and behavioral scientists. One of our 127

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projects evaluating a mental health initiative is currently in the process of determining how many individuals we need from each participating site for the treatment and control groups. In addition to the numbers needed to get enough statistical power in the study, we must also consider the different characteristics of the population in the study, hence the need for collaboration across disciplines and expertise level to design, implement, and evaluate different health interventions. My mathematics background and my experience with community-based work have positioned me at an intersection of disciplines in public health research, and helped place me in a work environment in which we strive to translate scientific research and statistical findings into policy recommendations. If I had the choice to start college again, I would not change my pursuit of a strong mathematical foundation.

Christopher Minck

Fixed Income Trader BlackRock Franklin & Marshall College BA Mathematics

After graduating college, I wanted a job which utilized my mathematical and interpersonal skills and provided learning and growth opportunities that would lead to a fulfilling career. A bleak job market provided few options. Finance interested me so I applied to every financial services firm I could think of. After months of sending resumes and a few temp jobs, I was offered a position in Trade Operations at BlackRock, the world’s largest asset manager. Over the next three years I worked in operations. I learned as much as I could about my role, how operations worked and how it related to other roles in the company. I worked hard to make myself valuable by collaborating on a variety of difficult assignments. It quickly became evident that BlackRock is a great place to start a career with several career paths that suited my skills and ambitions. As I learned about the different areas of the firm, I discovered that trading encompassed everything I was looking for. It required a high level of technical competence as well as strong communication skills. My big opportunity came a few years ago, with an opening on the Fixed Income Trading Team in London, UK. I relocated overseas and have had no regrets. Initially, I believed I was at a disadvantage having not studied finance at Franklin & Marshall. However, my mathematics degree and the analytical skills that I developed at Franklin & Marshall helped me understand the fundamental concepts of finance, like discounted cash flows for swaps, and the relationship between volatility variables. The trading team’s role is to execute our Portfolio Manager’s trade ideas in the market with minimal market impact and transaction costs. It is a fast-paced 129

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job. Our fingers must be on the pulse of the market at all times. Understanding the portfolio manager’s strategy is a vital part of our trading. It often dictates how aggressively we enter or exit their positions. Similarly, understanding market positioning and economic events’ impact on our markets is key to determining how and when to trade. A normal day for a trader starts at 7:15 am. The next hour is spent catching up on overnight news and a team meeting to discuss major economic events, market moves, and the day ahead. It’s critical to stay up-to-date on the market intraday as you can be called upon to trade at any given moment depending on a portfolio manager’s views. Trading is unique in that each trade is done solo. However, surrounded by your fellow traders, there is a lot of interaction and discussion regarding the best way to execute. Around 11:30 am our team usually has a heated discussion about lunch, which is eaten at the desk. Our trading day typically ends between 4:30 and 5:00 pm, when our index accounts are traded. After trading is done, we read market recaps, ensure all trades are booked, and work on side projects to improve productivity. Most days, we finish around 6:00 pm. The excitement of the market and the camaraderie of the team I work with make the days fly by. If a career in trading (or finance in general) interests you, be active early. Internships go far towards full-time placements. Financial institutions’ internship and graduate application deadlines are in early October, so start applying as soon as the fall semester commences. Be open to all opportunities that employers have to offer. There are a lot of interesting jobs that you may never have heard of. If you do not get the job you want right out of school, look for ancillary roles that allow you to work with the department you want to work for. No matter what role you are in, become the best at it. Learn how it fits in the overall organization and how your skills can add value to the company. This will maximize your chances when your ideal role becomes available.

George Mohler

Associate Professor Computer and Information Science Indiana University-Purdue University Indianapolis Indiana University BS Mathematics University of California, Santa Barbara PhD Mathematics

I currently work in “data science,” a field at the intersection of data analysis, mathematics, statistics, and computation. I focus on problems related to risk and human activity. For example, how can we use algorithms trained on past crime data to decide where police should patrol today or how can we use streaming data from a car to more accurately price car insurance based on usage? My collaborators and I have run experiments in Los Angeles testing algorithms for predicting crime against experienced crime analysts and found the algorithms to be about twice as accurate at predicting where and when crime is going to occur. Another project I recently worked on involved putting algorithms called neural networks on smartphones to determine if a phone is in a moving vehicle and if so, to track the mileage of the vehicle. While some universities are starting to offer degrees in data science, a mathematics degree is still a good route to take, and is how I got involved in my current job. In my daily work I use linear algebra, probability and statistics, numerical methods and optimization on a regular basis. At the same time, data scientists need to be able to implement their algorithms as software, so having at least a minor in computer science is a good idea if you want to go into data science as a profession. There are also a number of data science and machine learning competitions that are a good way to gain practical data analysis experience. There is a company called Kaggle that hosts many of these challenges that ask you to construct algorithms like predicting who will click on an ad, whether an EEG signal from someone with epilepsy is indicating they are about to have a seizure, or classifying the emotion of a person from an image of them. 131

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Environmental Products Analyst Element Markets Wofford College BS Chemistry and Mathematics BA German Rice University MS Environmental Analysis

As an undergraduate, I spent several summers working as an intern in energyrelated fields. The concept of how humans use energy – for transport, for work, for consumption of products – fascinated me. The production, delivery, and use of energy has applications across every discipline, and I was interested in how my technical ability in math and science could be applied in an international setting across languages and cultures. I gradually began to focus on renewable energy technology and sustainability, and this interest landed me in graduate school at Rice University as a master’s student in environmental analysis. Located in Houston, Texas, the energy capital of the world, I learned quickly how to differentiate between the different types of career paths available: from oil and gas to research to electrical utilities. My undergraduate and graduate studies led me to an analyst role at an environmental commodities trading firm. Our role in the industry is two-fold: to provide environmental products like carbon offsets and biogas, as well as to serve as a trusted advisor in the ever-changing environmental regulatory space. We work directly with project developers – from reforestation projects in the Amazon region, to landfill projects in the US – to provide carbon offsets to companies and organizations that seek to mitigate their carbon footprint. At a small company with ambitious goals and a global focus, my daily routine varies – from calling project sites to discuss purchase structures for their offsets, to conducting a feasibility analysis for applying offsets or biogas supply to a company’s carbon footprint, to possibly even building 133

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out a model to determine a company’s compliance obligation under California’s cap-and-trade program. The common thread here is that a deep understanding of math is not only useful, but invaluable in giving me the confidence to advise clients as well as independently seek out new opportunities for our company. Here is an example from the California cap-and-trade market: California sets a declining cap of CO2 emissions (measured in metric tons) for all entities that emit over 25,000 metric tons of CO2. There are a fixed number of allowances that are provided in quarterly auctions as well as allowances available for trade in a spot market. Pricing is dependent upon supply and demand as well as regulatory news, and, at a minimum, the floor price of an allowance increases approximately 7% each year. Our clients have fluctuating emissions year by year, but must mitigate the risk of their compliance burden extending through 2030. We develop models that incorporate emissions forecasts, supply and demand fundamentals, as well as regulatory changes in order to guide clients on an optimal path for complying with California’s laws. As a smaller firm, the employees work on an open trade floor – which means lots of opportunities for communication and collaboration. Due to the multiple emissions and greenhouse gas markets that our company operates in, it is vital to be able to transition between deeply analytical work (building out models and performing research on regulatory changes to environmental laws) and communicating effectively with the managers, lawyers, and accountants on the floor to ensure the trades are handled in an efficient manner. For those interested in the field of environmental markets and sustainability, having a keen understanding of lifecycle analysis, the regulations (both federal and state) that govern air emissions in the US, like the Clean Air Act, and persistence in networking are all valuable traits. Lastly, there are a surprising number of opportunities for students who attend sustainability conferences to network and find internships and jobs.

Tanya Moore

Vice President, Mission Advancement Goodwill of San Francisco, San Mateo and Marin Counties, Inc. Spelman College BS Mathematics The Johns Hopkins University MSE Mathematical Sciences University of California, Berkeley PhD Biostatistics

For most of my life I had hoped to find, like Dorothy in the Wizard of Oz, a yellow brick road that would lead me to my ideal career. But that path never materialized in any overt way for me. Instead, my professional journey has unfolded in segments over time, placing me on roads that seemed to divert from earlier directions. What propelled me forward was a desire for work that resulted in meaningful impact to the communities around me, and provided me an opportunity to create and be challenged intellectually. Fortunately, because I chose to study mathematics, I have a foundation that allowed me to move relatively seamlessly through jobs in public health, education, and workforce development. Working in a public health department in my hometown taught me about the intersection of community wellness, local government, and collective impact. My role involved coordinating a multi-agency collaborative focused on reducing racial and ethnic health inequities. The work required a strategic and systematic approach in order to move a diverse team with differing agendas forward. It also required creativity to design new community health programs and initiatives and relied on the ability to recognize and leverage areas of common ground among the stakeholders. When I transitioned into a role focused on improving educational outcomes for all students, from Pre-K to Post-Secondary, my experience in public health prepared me to support the management of another multi-agency collaborative process. While I had a learning curve to manage around education policy, my previous experience provided a framework for establishing and implementing strategies that resulted in broad changes across multiple institutional systems. Being trained as a mathematician gave me an innate approach to developing and 135

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analyzing programs in parallel. The ability to think through ideas and how to evaluate impact in a meaningful way served me well. While I have often desired a more streamlined career path, the irony is not lost on me that I now work in service to an organization that is focused on supporting individuals as they enter or in many cases re-enter into the workforce. As Vice President of Mission Advancement for Goodwill of San Francisco, San Mateo, and Marin Counties, my job is to guide the organization on how we can best deliver on our mission, providing second chances to individuals who have barriers to employment. In addition to managing a department that provides training and career services to employees and jobseekers in the community, my work involves designing programs, evaluating outcomes, managing grants, researching best practices and working with business leaders and community groups. My work is highly collaborative and there is no typical day. But, because of math, I have a strong foundation for problem solving, and thinking strategically and analytically. My background in statistics has given me concrete tools for managing and analyzing data and being comfortable with technology: important skills needed for my job. Over the last several years, outside of my formal jobs, I’ve been fortunate to work with an amazing group of women mathematicians to co-create the Infinite Possibilities Conference (IPC). IPC is a national conference designed to support and empower underrepresented minority women in mathematics and it has taken place at six different colleges and universities across the United States. It’s been a rewarding experience to have had the privilege to execute on a shared vision of an event that would encourage women around the country to experience a community that encourages them to stay on a path in mathematics and statistics. Math gave me a structure for ordering my steps and became a gateway for me to do what I care about, which is to support individuals in having the opportunity to live out their potential and to discover the intersections in life that bring about greater understanding and connection. If you are like me, and are unsure of where you want to end up, my advice is to focus on where you can begin. Start somewhere even if you’re not sure where it’s going to lead. It’s better to have a plan that you deviate from than to waffle with no plan at all. I’ve learned that progress along a path builds confidence, additional skills and a deeper understanding of what you’re interested in and what’s important to you. It’s all good information, and meaningful data points that can assist with building brick by brick your yellow brick road that leads to a fulfilling life and career.

Walter Morales

Technologist Chevron Corporation California State University Bakersfield BS Mathematics and Computer Science University of Southern California MS Petroleum Engineering

In simple words, my responsibility as a technologist at Chevron is first to solve problems of varying complexity and difficulty and then, if possible, to automate the solution I find. I get involved in different projects in the oil field, and I bring my expertise (coding and a capacity to solve complex problems) to help solve them. Usually I am involved in the development of tools to optimize and automate complex oil-field-related tasks. Here are two examples: • I was on the team in charge of developing a tool that creates anti-collision reports to help workers avoid collisions during drilling highly deviated wells. • I was required to find the three closest wells to a given well path to optimize temperature monitoring. To do this, I have used several programming languages (VBA, SQL, Python, etc.), Geographic Information Systems like ArcGIS, and some mathematics that helped me be a key part of the team assigned to solve these problems. I started at Chevron when I was recommended for an internship by one of my mathematics professors. I wanted to pursue a PhD in computational mathematics, but after weighing my situation at that time (I was relatively old to spend five to six years in graduate school, and the salary for the entry level job I was offered after my internship was very tempting), I decided to pursue a career in the Oil Industry. My day starts by checking my meetings and prioritizing my work for the day. I spend about 20% to 30% of my time attending meetings, and then I can focus on 137

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my work. I like my job because there is always a new project to work on, therefore it has never been monotone. I often get assigned to new projects that are challenging which makes my job fun and gratifying. I have work that is repetitive, but about half of my daily work is dedicated to new projects that last between six months to one year, which means that I have never worked doing exactly the same tasks for more than six months. I love the environment of my work. I have had the privilege to work with people from all around the world, since Chevron has operations in more than 80 countries, and I have learned to work with a diverse group of people – diverse in background, gender, culture, religion, and race – which has helped me to develop an appreciation of other people’s capabilities and to recognize and value performance above all. I also like that I have a flexible schedule: I can start work at any time before 9 am, as long as I work all the required time for the day, and I also get every other Friday off. Chevron usually gets interns from the mathematics department of the university I went for undergrad (CSU Bakersfield); this internship requires a professor recommendation and a GPA greater than 3.0. Meeting these two requirements helped me to get into the oil industry. The most valuable lesson that mathematics taught me was the ability to understand and solve complex problems. I never get intimidated by problems that seem complicated, and I enjoy spending time thinking of creative solutions and implementing them – a process that is very similar to solving new problems in mathematics. Therefore, in a way, I see my projects as I used to see my math classes: challenging, interesting, and intellectually stimulating. There have been many opportunities in which mathematics has helped me to contribute to the solution of problems at work. For example, with the help of some trigonometry, I was able to find the vertical depth of deviated wells in order to find the kick off point of sidetracks, and I used some calculus (calculating derivatives using numerical methods) when finding the rate of change in temperatures of specific parts of oil reservoirs. I think work/life balance is the most important part of work, and I find that when I spend more quality time with my family, I can perform better at my work. I am lucky that my company understands this and allows me to reasonably schedule my work around my family. I advise anyone trying to get a job in the oil industry to get an internship in any oil/gas/energy company, preferably during the student’s junior or senior year. More that 90% of the new hires in the industry come from internships. A high GPA will help, and coding is a great skill to have; these will increase the possibility of success in this competitive industry.

Janeth Moran-Cervantes

Software Development Engineer Amazon California State University Channel Islands BS Mathematics and Computer Science MS Computer Science

In high school, I did well in my math courses, and after my college-readiness teacher saw my interest in solving proofs, she suggested that I consider studying computer science. I attended Ventura County Community College for my requirements and prerequisites for my major (which ended up being mostly math and physics courses). I transferred to CSU Channel Islands as a double major in Math and Computer Science. It made sense because some of the courses overlapped. Without knowing what I was going to do with either major, I was simply trying to increase my opportunities. I didn’t see myself teaching in my immediate future but perhaps after having some experience. I didn’t know what I was going to do with my Computer Science degree, but I saw more attainable opportunities. I participated in mathematics summer research during my undergraduate years. In my senior year, I learned about machine learning and gained a greater understanding of how math was used in multiple algorithms that intelligently learned from data. This was the aha moment that led me in search of a field in which I could apply my math knowledge using computer science skills. After graduating as a double major, I joined the Computer Science Masters program at CSUCI. I was still not ready to make a move. At CSUCI, during the 139

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summer, I interned at tech companies, one of which was Amazon. Within Amazon, I leveraged internal mentoring resources to help me find a team that would be a good fit for me. As a result, I was introduced to an Applied Scientist within Personalization. After my return offer, it was clear that I wanted to work in Personalization at Amazon. It’s a data-driven organization that uses machine learning technologies, and I wanted to learn more. I joined Amazon without finishing up my Thesis for my Master Degree due to personal circumstances. I joined a newly formed team of four (manager plus three developers, including myself). I was a bit worried that development would be slow given the size of the company, but to my surprise, it was relatively fast paced. I had access to tools and a multitude of resources available. I was writing front-end code, testing, establishing a new team, and learning new technologies within the first month. Personalization focuses on providing a personalized shopping experience to every customer from the homepage to checkout. Concretely, Personalization owns features such as “Customers who bought this item also bought,” “Buy It again?”, “Recommended for you” and “Top picks” to provide a unique experience to each customer with the goal of helping them easily find and purchase the items they need. A developer within personalization may work on tasks such as improving front-end user experience, improving back-end datasets, testing, analyzing, experimentation and more often is responsible for the entire development pipeline from requirement gathering, deployment, experiment, to post analysis. The decisions we make are data driven. My math background has not only helped me write clean and reusable code, but it has also helped me understand the algorithms that power these recommendations, analyze the data, and make well-informed decisions based on it. I work with a variety of people from different regions, backgrounds, and roles to collaborate, teach, or learn from. Depending on the project, I may work from the office, home, a different building within the Seattle headquarters, and occasionally, travel to a different campus. One’s experience at Amazon differs from team to team. Within my team, we have meetings that include: bi-weekly operational meetings to review our systems, bi-weekly sprint planning, learning series, and meetings with other teams we may be collaborating with. We work collaboratively to complete projects and we have the flexibility to set our work schedule. It has been fulfilling to learn, move forward in my career, finish my degree, venture out (doing 206 bike rides, hikes, . . . ), engage in my local church, visit family multiple times a year, and look for ways to get involved in my community. Advanced mathematics is important and though it is not imperative for an engineer starting in Personalization, it is extremely useful if you have the background. For those interested in this field, I highly recommend having a strong statistics background and understanding basic machine learning concepts and algorithms. Most importantly, having a support system (professors, faculty, family, friends, . . . ) who can guide you and help you navigate through was fundamental in my ability to see myself in this position and work towards it. I have now been at Amazon for three years, am a second-level Software Development Engineer, completed my Computer Science Master’s degree, and am continuing to find my next challenge in the data field, which will require me to brush up on my math.

Elizabeth Morgan

Freelance Producer Bryn Mawr College BA Mathematics and Theater Yale University School of Drama MFA Theater Management

I spent most of my years in undergrad splitting time between my two biggest passions: math and theater. One evening might be spent working on problem sets with my math classmates, then the next I’d be performing in King Lear. I just loved getting to flex both my creative and quantitative muscles, and I wanted to have that opportunity in my career. So when the time came to decide what I would do after graduation, I applied to, and was accepted into, the Yale School of Drama Theater Management Program. At Yale, the program was a combination of classwork and filling actual fulltime roles within the Yale Repertory Theatre (Yale Rep), the professional regional theater affiliated with the school. There, I did everything from produce student projects at the Yale Cabaret to serve as Associate Managing Director of Yale Rep. One of the more unique experiences I had was spending two weeks in northern Vermont living with an avant-garde theater company, the Bread & Puppet Theater. The case study I wrote about their organization has since been taught at the University of Virginia Darden School of Business and the City University of New York’s Baruch College. Of everything I got to do at Yale, I had two roles I particularly enjoyed: the first was as Associate Director of Development. I loved the combined strategies of applying for grants and seeking donations, communicating about art, and socializing with potential donors. The second was Managing Director of the Dwight/Edgewood Project, an after-school program in which Drama School students teach local middleschoolers how to write their own plays, and then actually produce them. As Managing Director, I was responsible for budgets, schedules, and managing a staff that consisted of at least one future Oscar winner. But the best part was being able to use my skills and knowledge to help kids bring their imaginations to life. 141

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After finishing the program, I began seeking out development opportunities at theaters in New York City, and had the good fortune of being accepted for the role of Manager of Institutional and Government Relations at New York Theatre Workshop. My primary responsibilities were similar to those I had at Yale: researching and applying for grants, meeting donors, and communicating about the theater’s productions. Based on my math background, my role expanded to include helping the organization with budget management. It felt great using my skills to help bring great art to the stage, plus getting to attend an amazing array of performances, including the opening night of the Broadway musical Once. Despite having a tremendous passion for the arts, after a couple of years at the Workshop, I felt ready for a new challenge. So, after some exploration, I discovered the opportunity to join Collegiate School as the Campaign Associate on their capital campaign. Collegiate, founded in 1628, is the oldest school in the country, and it felt really special to be part of an institution and community so steeped in history. The school decided to construct a new campus on the Upper West Side of Manhattan, and it was my job to help raise the $100 million the project would need. My role involved researching prospective donors and creating briefs that included their histories with the school, their giving potentials, and the best ways to approach them. It was an amazing experience to help such a longstanding institution build a state-of-the-art home. Studying math didn’t just give me the ability to solve complex equations – it developed my problem-solving skills and ensured I would always understand the story the numbers tell, which is critically important when you’re soliciting donations or managing a theatrical budget. For young math majors who are looking to combine interpersonal skills with analytical skills, fundraising is a great career path. In addition to frontline fundraising, there is a good amount of analytical and research work. Fundraising software like Raiser’s Edge helps organizations store a tremendous amount of data about their donors, but they need employees with the ability to analyze and interpret that data in order to extract its maximum value. If you enjoy attending social events and being an active part of a non-profit community in addition to applying mathematical thinking, fundraising can be the best of both worlds.

Carol Muehrcke

Independent Cyber Security Consultant Reed College AB Mathematics Rutgers University PhD Mathematics

I work as an independent consultant in cyber security. Specifically, I am the ISASecure project manager for the ISA (International Society of Automation) Security Compliance Institute (ISCI) industry consortium. I also work on governmentfunded research projects. ISCI develops ISASecure certification programs that certify the cyber security of industrial control devices and systems. In my role I am privileged to lead and to follow a group of roughly ten representatives of industrial equipment suppliers, oil and gas industry users, and test labs, all with a dedication to raising the bar in resilience to cyber attack. The immediate practical benefit of this work is gratifying. For my research projects, the payoff is farther off. A recent project has been to develop a generic method to model an arbitrary networked computer system, to simulate its security performance under cyber attack. Modeling and simulation is a common approach taken for other kinds of performance engineering, but is not commonly used for cyber security. Early in my career, I read and believed a “futures” book that argued that the issue of cyber security would change the world. When an opportunity in that field appeared, I felt sure it was a good move. An organization was looking for individuals with advanced degrees in mathematics to use theorem provers to “prove” that a new operating system was secure. Use of this approach was relatively short-lived, but the opportunity put me in the field of cyber security near its beginning. All of my subsequent jobs in this field were found through colleagues at this first company. The ISASecure project manager role evolved from what was originally scoped as a three month specification drafting task, nearly a decade ago. As ISASecure project manager, I identify topics and lead technical committee discussions ranging from which product types most need certification programs, to the network traffic 143

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rate and statistical confidence required for network flooding tests. I draft specifications and address comments. A less normal day is to fly to China to assist a developer applying for recognition of their test tool for compliance with ISASecure specifications. Signing in as a college freshman, I stated my major was Mathematics. “Pure or applied?” they asked. “Pure,” I answered, with no hesitation. However later history found me continually working the balance between pure and applied. Near the end of graduate school, I began to feel unsure about my envisioned career path as a math professor. The pure academic environment and long-term teaching requirements as I now understood them no longer felt right for me. As a career options backup plan, I audited the first two semesters of undergraduate computer science. This background was enough to be hired by Bell Laboratories and launch a career in the computer field. My Bell Laboratories assignments were distinctly “applied” types of analysis: engineering economics, optimization algorithms related to manufacturing operations, writing requirements and standards for software systems. I attempted unsuccessfully to seek out more research-oriented assignments. I was promoted to supervisor, and out of self-preservation took a course in time management. I’d suggest it sooner. I studied abstract algebra. The more abstract, the better I liked it. Some of my work has directly used mathematics or formal logic, though not the majority. However, I have found that identifying the right terms, definitions and structure within which to talk about any topic is a universally applicable skill. Likewise is understanding what is or is not a solid argument, and how to write it down. In my recent research, I developed concepts, terms, and axioms required to model the cyber security performance of an arbitrary networked computer system. I researched the common types of cyber attacks to ensure that the simulation model could represent them. I am very happy at this point with the freedom to work from home and integrate my work as I see fit with other parts of my life. Prior learning and interaction with others in a structured office environment (20 years) has enabled me to operate in this mode. Focusing on a topic you love (in my case abstract algebra) gives depth and confidence. Being open to learning outside of this area can lead to unanticipated opportunities. At a higher level, I found it invaluable to study the direction the world was heading so I could recognize a range of ways I might participate in it. An interesting area I have noticed recently is mathematics associated with genetics. Do not take your planned or expected path as a given. The best jobs may not have a simple description.

Grace Nabholz

Research Mathematician US Army Corps of Engineers Research and Development Center Mississippi College BS Mathematics

Throughout my time at Mississippi College, I always wondered what I would do with my math degree come graduation. It wasn’t until after I interned at the US Army Corps of Engineers (USACE) Engineer Research and Development Center (ERDC) Information Technology Laboratory (ITL) that I got my answer. Upon graduating, I started working full time as a Research Mathematician at ERDC where I develop mathematical and statistical models of phenomena for computational simulations, perform computations and apply methods of numerical analysis and statistical analysis to data, write Python and R scripts for local machines and high performance computers to further the capability of data analysis, create 3D environmental models using software, create automated workflows for running scripts and producing results, and help write technical reports, research reports, and funding proposals for completed, ongoing, and future projects. I work more at a computer than I ever expected, but my work environment is very collaborative, and interaction with my teams is vital to accomplishing our goals. One of my favorite projects so far has been with a large group of data scientists who rely on regular team meetings and collaborative workdays to analyze data and implement machine learning strategies to better understand our data and our project. ERDC is diverse, and my branch at ITL is a melting pot of various cultures, nationalities, and education backgrounds. Our teams are comprised of PhD-, Master’s-, and Bachelor’s-level employees. Computer scientists, computer engineers, mechanical engineers, civil engineers, physicists, aerospace engineers, biological engineers, and mathematicians all have offices down our hallway and work collaboratively on interesting projects! 145

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If someone is interested in a position like this, I would suggest taking computer science courses. Though I am a mathematician, programming and computer science are necessary to complete the math my team needs me to do. I had some exposure in undergrad, but I regret not taking more CS classes—I, like many others, just did not realize how vital it is today. One of my favorite aspects about my job is that I’m always learning! The projects require a deep understanding of math and science and involve infinite opportunities to apply mathematical modeling to a variety of interesting projects. Because I work for a research-based institution, everyone around me is constantly learning and exploring new topics, new concepts, and new ideas. ITL, in particular, offers many opportunities to expand our knowledge through training courses on interesting subjects and regularly scheduled talks from other professionals to share their research and findings. As a “new adult” who’s just joined the working world, adjusting to corporate life has been an adventure! Some days, I’m all too ready to leave work at work and invest in my life at home. Other days, work is so interesting that it’s hard to put down! Finding a healthy balance between work and home is crucial to staying happy and eager to work. I am also working on my master’s in applied math, so my schedule is jam-packed. Time management and work/home equilibrium affects everything, so it’s very important to balance well and make time for the things that really matter. For mathematicians interested in starting their corporate careers, I highly recommend exploring opportunities in Information Technology Research and Development.

Aisha N´ ajera Chesler

Associate Mathematician RAND Corporation Universidad Nacional Aut´onoma de M´exico Lic. Matem´ aticas University of Arizona MS Mathematics Claremont Graduate University PhD Applied Mathematics

My love for math started at a young age. I think I pretty much decided back when I was in middle school that I would become a mathematician. I liked attending math club and participating in math competitions because I got to solve problems that I had never seen before and for which there were no prescribed paths to solution. Right after college, I moved to the US for grad school. I was very enthusiastic about studying convex geometry and becoming a professor, but things didn’t work out as I had planned and after finishing my master’s I started working as a consultant. I worked for IBM for almost three years doing SAP implementations. SAP is an enterprise software to manage enterprise resources, business operations, and customer relations. During that time, I learned a lot about technology and technical sales for multi-million dollar companies. I learned about business processes and different industries. I improved my soft skills and became a better communicator. It was a challenging process because I am a naturally reserved person and English is not my first language, but I think that struggle has paid off throughout my career. As time went by as a consultant, it became clearer to me that I missed doing research and math. At IBM it was easy to connect with other lines of business within the organization, so I took advantage of that opportunity and started setting up informal meetings with people working at IBM’s research labs around the world. I wanted to learn about the work they were doing and about their careers and the sort of tools they were using. I decided that I needed to learn how to program, that I knew almost nothing about what a mathematical model was, and that most, if not all, researchers had a PhD. I went back to school enthusiastically but also with a great deal of self-doubt and insecurity. However, I was very fortunate because 1) I had been accepted into 147

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a program that was very flexible, 2) I got to work with an amazing and supportive advisor, and 3) I was surrounded by people who wanted to see their students succeed. Working and looking for a job after my masters also gave me a perspective on the demands outside of academia, so I approached my studies with two possibilities in mind: one of staying in academia and the other of working outside of it. Therefore, while I attended academic summer schools and conferences, I also applied to internships that had a research focus. That is how my career at RAND started, as a summer associate. I have been at RAND for almost three years. I enjoy working here because it is a flat organization and it is very flexible. I work from home one day a week and, on other days, I am in the office from about 6am to 2pm. That allows me to spend the afternoon with my two daughters and avoid some traffic in the LA area. At any given point in time, I am usually engaged in four projects, though some days I just work on one or two at a time. The projects usually last about a year, and while a big part of the research is done in solitary, we do meet with our project team and there are plenty of opportunities to collaborate and discuss. Each team varies in size, but could have anywhere from three to nine people or more. The composition of the team varies and I could end up working with other mathematicians or with engineers, operations researchers, statisticians, economists, physicists, sociologists, historians, etc. Projects are not assigned, but rather you must convince the principal investigator leading a project that you will be a good contributor and a good team player. For the past few years, I have worked on projects in the areas of military logistics, cybersecurity, and health care. I have been doing analysis of the Army’s logistics data and working on various business intelligence and data science projects that provide better insight into operations and decision-making.

Andy Niedermaier

Trader Jane Street Capital Harvey Mudd College BS Mathematics University of California, San Diego PhD Mathematics

A big part of my job involves discovering and refining mathematical models relating to the prices of various securities (such as stocks, bonds, commodities, etc.). It’s a very collaborative, academic environment. I use the word academic because my coworkers and I simply want to learn as much as we can about how the world works: the more we can learn about, say, how changes in the price of oil impact global interest rates, the better our trading will be. There is one crucial way in which my job differs from that of an academic math PhD: unlike my math courses in college and grad school, which were all about finding proofs, working in the “real world” means never having perfect models or perfect information. Models are continuously under development; a news event or regulatory change might cause a good model to cease being good. Finance was Plan B to me when I was in grad school. But when Plan A (academia) yielded no job offers, I applied to a handful of well-regarded quant funds, and here I am today. And I’m glad I wound up here! The work-life balance is quite good: a typical workday runs from 8:00 am to 5:00 pm. I don’t work weekends or work extra time from home. My free time is my own, and I quite like that about the job. We’re a little spoiled, too: fully stocked kitchen, free lunch, on-site gym, I could go on. Most of my coworkers were math, natural science, or computer science majors in college, and most of them came to Jane Street fresh out of college. (PhDs are in the minority here.) We’re all at least a little bit nerdy—you’ll often find Jane Streeters hanging out after work to play chess, go, poker, or whatever complex new board game someone is itching to try. When I travel to campus career fairs or information sessions to recruit on behalf of Jane Street, I’m often asked by students for advice. The thing I usually say is 149

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this: apply for jobs. Do it sooner rather than later, and do a lot of it. Do it as soon as you are a freshman in college (or early in grad school). Why? So that you can get all your awkward, nervous, dive-bomb interviews out of your system as early as possible. So that you can gain a good sense for what interviewing is like, and how to excel at it. And so that you can get summer internship offers! Even though you may love math and want to do math research every summer—as I did throughout college and grad school—I urge you to seriously consider seeking and taking at least one summer internship in industry, maybe more. You’ll gain realworld work experience, broaden your post-graduation options, learn new things, and much more. (And you might earn a fair amount more than at a summer research program.) Perhaps most importantly, by throwing yourself into the interviewing and internship world and giving it a real try, you’ll be giving yourself the best chance to end up in the spot that really is best for you.

Jacqueline Nolis

Director of Analytics Marketing and Sales Strategy Firm Worcester Polytechnic Institute BS Mathematics MS Applied Mathematics Arizona State University PhD Industrial Engineering

I’m the director of analytics at a marketing and sales management consulting firm. The firm specializes in helping companies come up with strategies around marketing and sales, including: how to best acquire customers, how to design loyalty programs, and how to bring new products to market. The firm realized that they were missing opportunities because most of their expertise was on the business side. They had many questions that could be answered using company data but didn’t have the experience to do it. I was brought on to build a team of math and data experts who could help improve the strategies by analyzing the data the company has. Analytics (also called data science) is the task of taking data from within a company and using math and statistics to gain insights into how the company should run. This can include analyzing customers to determine which product to recommend selling them, taking sales data and forecasting future revenue to make planning decisions, or using previous orders to determine the best price for a product. The job requires understanding math and statistics, knowing how to query a database and write code to analyze the data, and understanding business enough to infer what the right solution is. My job is split between managing analytics projects, helping sell new projects, and doing the data analysis to deliver solutions. The types of analysis I do fall well into the field of data science: regressions, clustering, time series analysis and forecasting, etc. Those are the techniques we use on the data, but when it comes to the math side of the job the majority of my time is spent cleaning the data: figuring out how to join datasets together, how to overcome missing data, and understanding assumptions inherent in the data to get it ready for analysis. I think this is true for most data scientists, honestly. 151

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My work environment is very social and collaborative. We have an open office where most of the employees work in one room. I really enjoy it because I’m a social person so I get to interact with lots of people throughout the day and hear what’s going on for different projects. That said, I’ve worked at other companies where each employee has their own office and there is much less of a social aspect. There are benefits to both; it just depends on your personal style as to what you prefer. Here is an example of my work day, taken from my calendar last week: 8:00 am Go to a meeting where we discuss a potential new client project that would require data analysis. 9:00 am Work in R on analyzing data for an existing project, either preparing it by cleaning it and joining it to other datasets, or running regressions, clustering, or other machine learning methods on it. 11:00 am Have a meeting with a junior employee around the work they are doing on a project, and help them craft the next step in their analysis. 12:00 pm Lunch. 12:30 pm Have a meeting where we discuss the progress of an existing project with the client over the phone. We show them what we’ve done so far, and they give feedback. 1:00 pm Have a meeting with HR around what we’re looking for in the next candidate to join the analytics team. 2:30 pm Take the results I produced in R earlier in the day, adjust them, and then put them into a PowerPoint deck. 4:00 pm Meet with several other employees to discuss developing some new materials to help promote the company and sell business to new clients. My degree in math opened a lot of doors for me. The field of data science only started existing in the past ten years, so I was able to get in while it was still blooming (and thankfully it’s still blooming to this day). There isn’t a universal curriculum for data science, so companies have to look for people in other fields, including mathematics. Having a math background also gave me experience in thinking critically around how to solve a problem, which you need to do constantly in the field. A data science position doesn’t have very much pure math in it, meaning, you don’t tend to spend your days thinking about theorems or trying to develop totally new methodologies. Instead, you take existing methods and try to figure out how to apply them to your particular data. So knowing what different mathematical and statistical methods are out there helps immensely, as well as just having the ability to think in numbers, patterns, and trends. I think the general way to get into the field of data science consulting is to build up a strong background in (1) math and statistics, (2) programming and databases and (3) business. A classic path for this is to start by getting a degree in math or statistics and getting an internship or two along the way, then going into industry to get the business and programming experience. The more of an even distribution in those three buckets, the easier it is to get a job! An example of a problem I worked on during my career was for a company that sold custom machinery to factories. Each machine was individually designed, but before it was designed and built they had to tell the customer what the price would be. Sometimes the machine ended up costing well below what they originally

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priced it at, and sometimes well above (causing the company to lose money). They brought me in to try and determine how to better price their machines. What I ended up doing was taking their historical data on the machines they made previously, and used some advanced regressions to predict what the cost of the machine would be before it was quoted. Not only that, I would also predict what the variance of the outcomes could be. From there, the company could look at the possible outcomes and determine a price that would make them money at least 90% of the time. This ended up helping the company increase profitability, and it was done by taking their data and applying math and statistics to it. My job has a great work/personal balance, because I have made both parts of my life important to me. I think for this kind of work you don’t actually get much of a benefit from working long hours: usually you need time to sit and stew on the problem and more hours doesn’t make that go faster. Also, often you’re waiting for the client to send you data or answer a question, in which case there isn’t much you can do. That being said, there are weeks where, due to the needs of the project, I have to work long hours, but the lighter weeks even this out. A couple pieces of advice. First, try your hardest to get an internship or two while you’re in school. Internships are great because they teach you what it’s like to work at a company and how to engage in corporate culture, and, later, when you’re on the job market, companies will see the internship on your resume and they’ll know you’ve been exposed to the open environment of working at a company. Industry is very different than school—in school you have a very welldefined problem with one right answer, whereas in industry, everything is openended and often you don’t even know what the true problem is. Second, during my career the act that has propelled me up the ladder the most is finding new areas of opportunity and working on them. Here is an example from my first job, which was at Vistaprint, an ecommerce company. I noticed that there was a potential way for us to use statistical quality control to alert marketing to when sales were below expected volumes so they could try to increase them. No one told me to work on this, I just noticed it was a need for the company so I did it. This got me recognition throughout my team, and I got to lead the project to build the capability. Finally, the best skill to have is the ability to learn new skills. During your job, you’ll constantly be running into problems you’ve never seen before, so the ability to open a book or web browser and start researching solutions is critical to success. If you learn how to learn, everything else comes in time.

Kyle Novak

AAAS Science & Technology Policy Fellow US Agency for International Development Deputy Chief Analyst (former) US Air Force (retired) University of Wisconsin–Madison BS Mathematics and Physics MA Mathematics PhD Mathematics

When I was working on my college degree, I never imagined that I’d one day be hopping a cargo plane to Japan to help relief efforts following one of the worst earthquake, tsunami, and radiological disasters in history. In the military, you need to be ready for anything, even as a mathematician. I went to college on an Air Force ROTC scholarship majoring in math and physics. The scholarship came with a four-year service commitment, and I saw it as an opportunity to serve my country and figure out what I wanted to do with my life. What I thought was going to be four years in uniform ended up being over twenty-one, spread across the world. My first assignment out of college was at the Air Force Research Laboratory. I was a member of a small skunkworks red team playing the role of an adversary and trying to see just how difficult it might be to build a cheap, autonomously guided cruise missile using only off-the-shelf technology. I researched flight dynamics; designed a flight simulator from scratch; wrote guidance, navigation, and control algorithms; and conducted post-flight analysis. (Our missile crashed.) The military moves its people every few years, building leaders through diverse experiences and challenges. So, three years later, I started a new assignment as a cryptanalyst for the National Security Agency, where I solved complex mathematical problems. Another three years later, I guided flight test engineers on the design of experiments and statistical analysis on everything from night vision goggles to close-formation, humanitarian airdrops. The Air Force needs technical leaders and often invests in its officers by sending them to get advanced degrees. For me it was a PhD. As payback for my new degree, I’d spend the next several years teaching applied math to 155

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graduate students and researching computational methods for quantum mechanics and high-temperature superconductors at the Air Force Institute of Technology. The second part of my career became increasingly focused on supporting Air Force operations at staff headquarters. Mathematicians help senior leaders by providing objective and cross-cutting decision analysis, operations research, data science, and mathematical modeling. I supported NATO operations in southern Afghanistan, where understanding indicators of development, security, and governance were integral to assessing progress of the counterinsurgency campaign. Later, while assigned to the Air Force’s warfighting headquarters in Hawaii, I supported air and humanitarian operations across the Pacific, from California to India and Alaska to Antarctica. Occasionally, this required a small degree of math under pressure, like quick-turn analysis at 4 am for a 6 am decision briefing during round-the-clock crisis operations. I finished my career serving on the air staff at the Pentagon where I led a team of analysts to develop the network risk model that the Air Force now uses to help prioritize its major programs. This involved explaining mathematical concepts plainly and succinctly so even a fighter pilot could understand and garnering support from key stakeholders on a novel machine learning methodology. I retired from active duty military service to focus on science policy and international development, working to end extreme poverty and promote resilient, democratic societies through better use of science, technology, and innovation. I can only imagine where this next career in mathematics will take me.

Dean Oliver

Vice President of Data Science TruMedia Networks Caltech BS Engineering & Applied Science University of North Carolina MS Environmental Science and Engineering PhD Environmental Science and Engineering

I work in sports analytics or, as popularized in books and movies, I do “Moneyball.” I wrote a book, Basketball on Paper, at the same time that the book Moneyball was being written (2002). Moneyball was about how the Oakland A’s baseball team was using statistics to identify undervalued strategies and players. My book was more a handbook on how to use statistics to build a better basketball team through player selection, style, and strategy. When Moneyball came out and was a bestseller in 2003, people in basketball read it and wanted to know how to do it in their sport. When Basketball on Paper came out eight months later, I was able to offer it as a guide. That was when I left environmental consulting for sports. I started by working with NBA teams: the Seattle Supersonics, then the Denver Nuggets. The NBA life is a bit unstable, involves a lot of travel, and jobs can come and go at the whim of an owner, so when the lockout came in 2011, an opportunity came to join ESPN, where I worked for several years. I now work at a company, TruMedia, that provides analytical databases and business-intelligence engines to sports teams and media. The work I do is about building metrics and analyses to better understand sports. I’ve done this over a long time in basketball, with recent work in football. My current work in basketball is building models for how defense works, how players collaborate to stop the offense. These models are a mix of classic statistical methods and more functional models of the game. Since joining ESPN, I have also done a lot of football work. American football is a very different sport, and building models for that requires much better knowledge of the state of the game, so there are a lot of classic statistics that are needed there. The framework for understanding football is still being constructed and will get a big boost when the NFL releases player tracking data it has started collecting. 157

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My engineering degrees involved a lot of statistics, programming, and differential equations that describe environmental systems. The statistics and programming come in handy on a regular basis for predicting player performance, estimating the chance of a shot going in given a defensive configuration, and just making models to predict games. The differential equations are more useful conceptually—the concept that there must be conservation relationships, for instance. You can’t have an algorithm give credit to players that sums to four points when only two points were actually scored. There is also a lot of geometry and trigonometry in dealing with the new basketball player tracking data that shows where players are throughout the game. Knowing whether a defender is moving fast enough to cut off a lane between the player with the ball and the basket—that is a mathematical physics problem. The job is incredibly satisfying. I use what I learned in school far more than I ever did in environmental consulting, plus I continue to learn new and challenging things every week. The job does require a great knowledge of sports—ideally from a coach’s standpoint—but knowing databases, programming, and statistics have all been critical to my ability to proceed. I do feel that knowing sports and having good mathematical skills is the best combination in order to do my job.

Laurel Paget-Seekins

Director of Strategic Initiatives Massachusetts Bay Transportation Authority Oberlin College BA Mathematics and Liberation Struggles Studies Georgia Institute of Technology MS City and Regional Planning PhD Civil Engineering

My job is never boring. Each day is a new set of problems to solve, large and small. I currently have two main roles at the MBTA (the fifth-largest transit agency in the US). The first is that I help design and implement policies for both fares and service. My role is as the facilitator and translator between the decision-makers, who mostly think about ideas at a very high level, and the operations staff, who are focused on the multitude of details it takes to implement a new policy or program. My second role is that I am one of the directors of the Office of Performance Management and Innovation for the MBTA and Massachusetts Department of Transportation. Our department has a leading role in gathering disparate data sources, analyzing data, and building performance tools to help our management and the public understand our performance and what can be done to improve it. (See www.mbtabackontrack.com for an example.) We have datasets that are very large and automatically generated, like all of the transactions on our fare collection system and all of the records of our vehicle locators. We also collect data using passenger surveys, going out in the field and doing visual observations, and by designing pilot programs to answer research questions. We mostly use basic statistics to design data collection efforts and analyze data, and occasionally we build more complicated models. My math background was necessary for my graduate work in civil engineering (graph theory is very useful for transit network design), and it helps me to understand the data analysis component of my job. But I also think my math degree helps me have the skills to act as the translator between the ideas people and the details people. Math is a good training for being able to understand both directions; sometimes you have a bunch of details and you put them together to find 159

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the larger idea, and sometimes you have an idea and you have to find the details to know if the idea is supportable. My normal day involves going to meetings, checking in with my staff between meetings on all of the projects that we are doing, and, in the evenings, writing and reviewing policy documents. I oversee a team of six employees and a small army of interns, and I manage the research partnerships we have with universities. I have worked with students in civil engineering, city planning, computer science, mathematics, political science, economics, and other fields. My pathway to this job was rather circuitous, but I find my diverse experiences to be really helpful. I started as a transit advocate when I was in graduate school, and then worked as a postdoctoral fellow doing academic research in Germany and Chile. Based on the networks I built in the industry, I was lucky enough to get hired at the MBTA with a lot of freedom to build my department and work on the issues I find important. But it means that I currently have no work-life balance. My advice is that often careers don’t take the shortest path between points. I am never quite sure where I am going next, but I am confident that it will be interesting. I am successful in my current position only because of all the insight I have gathered along the way in very different settings. Analytical problem solving skills are needed just about everywhere; there is no end to difficult problems that need to be solved.

Christine Papai

Deputy Country Director Innovations for Poverty Action Ghana Carleton College BA Mathematics University of Minnesota MS Mathematics MDP International Development MPH Maternal and Child Health

There’s a scene in the 2003 movie Beyond Borders where Sarah (Angelina Jolie), a freshly self-identified humanitarian of wealthy means, has her first encounter with the poverty and famine known only in the developing world. While visiting a relief camp in Ethiopia, Elliot (Noah Emmerich) introduces himself as the chief administrator and logistician, “if that doesn’t sound too pompous,” he says. This idea of a humanitarian “logistician” got the gears turning in my head. Surely there were even more ways that I, someone whose mathematical accomplishments to date were seen only on transcripts, could use these skills to help reduce the global burden of poverty. As it turns out, I didn’t end up working in logistics, but in another niche of international relief and development that relies heavily upon mathematics: impact evaluation. Impact evaluation is the assessment of an intervention in order to determine what outcomes – both intended and unintended – are directly attributable to the intervention itself, separating true cause-and-effect relationships from outcomes that happened coincidentally. The gold standard in impact evaluation methodology is the randomized controlled trial (RCT), familiar to many for its use in medical trials, and this is what my employer Innovations for Poverty Action (IPA) specializes in. IPA is a research and policy non-profit that brings together researchers and decision-makers to design, rigorously evaluate, and refine these solutions and their applications, ensuring that the evidence created is used to improve the lives of the world’s poor. IPA works in many sectors of development, including agriculture, education, finance, governance, and health. I work as the Deputy Country Director in IPA Ghana’s Accra office. In this role I manage a portfolio of research projects, guide the development of new projects, lead the organization’s engagement with the 161

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health sector, and oversee the office’s finance and administrative teams. In a given week, I might help a Research Associate interpret daily statistical checks of data collected from a survey on the impacts of secondary education, draw up a budget for a project studying the impact of asset loans to small and medium enterprises, plan an event centered around the use of mobile technology in health initiatives, train staff on a new budget tracking tool, and calculate how many motorcycle helmets our survey teams will need during peak times. There is never a dull day, and the diversity of my responsibilities – as well as the threads of mathematics woven throughout – keep me engaged with my work. I am drawn to evaluation because it combines the quantitative with the social, helping ensure resources are used efficiently and effectively for the greater good. My background in mathematics has given me an edge in understanding the complexities of the models behind impact evaluation, which enriches my conversations with the top-notch researchers who design IPA’s studies. Studying mathematics has also helped me understand the programming and coding languages used at IPA. SurveyCTO and STATA are what we use daily for data collection and analysis, but Excel is the program that cuts across all activities and departments, and I encourage every mathematician to become an Excel wizard—not just because I think it is fun to use, but also because it makes your work even more efficient, making you even more invaluable to your employer. To those who are interested in living abroad, especially in a developing country, I highly recommend pursuing study abroad opportunities, fellowships, internships, and research projects in places that will stretch you beyond your comfort zone and help you build your cross-cultural skills. Gaining experience abroad also gives you an edge in the recruitment process when hiring managers are comparing candidates with similar skills. Another key step was my training in statistics and evaluation (both quantitative and qualitative), especially at the graduate level. Master’s degrees are becoming more of a norm for people in international development research and evaluation, especially in fields like Public Affairs, International Development, and sector-specific disciplines like Public Health and Economics. And for those aiming for management positions, supervisory and management experience is highly valuable, even if it’s not in a research or evaluation setting. Reflecting on my career path to date, I can see that each of my jobs and degrees has helped me get where I am today, but it was along a meandering path, not a direct one. I jumped from business consulting, to nonprofit management, back to graduate school, and then to a technical evaluation job, before I ended up where I am today. I think it is so important to enjoy the work you do each day and to be patient with yourself, trusting that what may seem to be “odd jobs” are forming together to launch you into what could be your “dream job” someday.

Yolanda Parker

Mathematics Professor Tarrant County College Texan A&M University BS Applied Mathematical Sciences Dartmouth College MA Liberal Studies Illinois State University PhD Mathematics Education

I am a professor in the mathematics department at Tarrant County College, a two-year community college located in North Texas. After earning my Bachelor’s degree from Texas A&M University I became a middle school mathematics teacher in the Fort Worth Independent School District. At that time, most of the professional development workshops I attended provided tools for teachers to incorporate writing across the curriculum. Even though I was doing a good job at providing more opportunities for my students to write in mathematics, I wanted to improve my own writing. One of my middle school teacher colleagues recommended the Master’s degree program she had just completed at Dartmouth College. It was convenient for educators because of the option to earn a Master’s degree in six years by attending classes only in the summer. The Master of Arts in Liberal Studies program took me out of my comfort zone and placed me among several English and History teachers, and into interdisciplinary sociology courses where I had to do my fair share of writing. With every opportunity, I would relate my writing to mathematics. For instance, in one class we read a novel about a family that was set during the French Revolution, and in my reflection paper I related it to a revolution in the sine curve. I enjoyed facing and overcoming the challenge of the courses in the program so much that I wanted to continue my focus and not stop at the end of each summer. As a result, I resigned from my teaching position to take classes throughout the year and finish in less time before returning to the district. However, I didn’t return 163

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to the district; my time as a classroom teacher in a K-12 setting came to an end, and my higher education career began. While at Dartmouth, I started applying to graduate school to earn a doctoral degree in Curriculum and Instruction with a concentration in Mathematics because I had no idea that a Mathematics Education degree even existed. Through my search and research, I found the Mathematics Department at Illinois State University and saw that they offered a doctoral degree in Mathematics Education. After visiting the campus and meeting students already in the program, I knew that Normal, IL, was the place for me and I have never regretted that decision. I am now a mathematics educator, where I teach future teachers – a direction I never considered choosing for my career, but I am glad it found me. Instead of just teaching and learning mathematics, my students and I discuss the meaning behind the concepts so they will be better prepared to explain mathematics and answer questions when they are teachers in their own classroom. Even though research is not required in my current position, I have recently been involved with two ongoing research projects. With one team of researchers, we are providing tools to help teachers empower students by making mathematics relevant to all learners through cognitively demanding culturally relevant pedagogy from a non-deficit perspective. This helps mathematics students critique society relevant to their lives and to use their cultural knowledge. As part of another team of researchers, I assisted in developing an algebra teacher self-efficacy instrument by developing items based on a content analysis and then conducting an exploratory factor analysis in two phases to refine the number of items to include. The instrument assesses algebra teachers’ perception of their knowledge and ability to teach algebraic concepts and can be used by mathematics teacher educators to examine need and impact of professional development. The instrument can also be used to provide support for mathematics teacher educators who are working with in-service teachers in the field.

Karoline Pershell

Lead Technical Researcher Zenti, Inc. University of Tennessee at Martin BS Mathematics, Physics Minor Rice University MS Mathematics PhD Mathematics

I transferred to the University of Tennessee at Martin from a private Catholic all-women’s college near my home in Indiana to pursue bull riding at the collegiate level. I don’t exactly remember, but I think the conversation with my parents went something like: “Mom, Dad, I want to leave my full-ride academic scholarship at a private women’s university to attend a school you have never heard of, in a state you have never visited, to pursue something I am not very good at.” I may be paraphrasing, but I think my parents said something like “Karoline, that is the smartest decision you have ever made.” And it turns out they were right. I worked hard in the classroom, I worked hard at the practice pen, I worked hard in the gym, I worked hard when no one else was watching. That was the piece for me: I wasn’t doing this to change a system; I was doing this for me. I was doing this because I wanted to be MORE, and I found a place where I was challenging myself and my boundaries and I loved it. Bull riding alone doesn’t make for a great career. It was only a short (but unconventional) piece to my career (and likely the least lucrative). So what have I done since bull riding? I actually completed a major in math and a minor in physics at UTM. (I didn’t tell my rodeo friends I did math, and I didn’t tell my math friends I did rodeo. They just seemed like two separate crowds.) And then I went to get my masters and PhD in theoretical math. That was good, but I slowly started to pull away from academia, to get one foot out and keep one foot in – I didn’t completely leave (because I wanted the best of everything), but I wanted to do MORE. But I didn’t know what “MORE” was. Or where you find MORE. Or how you actually do MORE when you find it. I just wanted to do MORE. That’s not a lot to go on, but luckily I have never felt the need to make decisions based on clarity 165

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of outcomes. You balance the risk and decide if you are going to jump. So I took chances. When an opportunity came up, I asked two things of myself: Self, does this use your skills? Self, does this look interesting to you? I did NOT ask, “Where do I see myself in ten years?” or “What’s the right path to get there?” I had a nagging inner voice that said, “You can do MORE,” and a level of judgment that merely said, “Yup. This sure looks like MORE. You should go do that.” So: (1) I completed my Masters and PhD in theoretical mathematics under the brilliant 3-manifold topologist, John Hempel; (2) I taught at the University of Tennessee at Martin as an Assistant Professor of Mathematics; (3) I did research on reversible hydrogen fuel cells with a brilliant retired British physicist who had started his own winery in west Tennessee; (4) I hopped on a plane to China to teach math for a summer with very little information before I got there, and under some potentially shady circumstances; (5) I tossed my hat in the ring for a Fulbright position and jetted off to India to live for seven months and teach Masters students and work and write; (6) I applied to the American Association for the Advancement of Science and was accepted in their fellowship position, and I learned a lot about how to get things done in a large bureaucracy, how to create coalitions, lead projects, and then get out of the way when others have better ideas; (7) I worked in Washington, DC, at the Foreign Service Institute, the training wing for the Department of State, where I was the Evaluation Coordinator and led a coalition who established the policies, standards, and guidelines for evaluating how we train diplomats; (8) I got approached through LinkedIn by a Silicon Valley tech start-up that does machine learning on social media data, where I now work to develop research design plans to test and verify our language learning algorithms. Sometimes, this “career path” feels like anything but a CAREER in the traditional sense of the word. Paths like this happen because a task comes up and you don’t have time to say, “I don’t know how to do that.” You have the knowledge, skills, and attitude to know that it is a manageable task, so you just dig in, get started, and see where it leads. For me, it has always led to another open door.

Cara D. Petonic

Director, Corporate Strategy Comcast Corporation Bryn Mawr College BA Mathematics, Dance Minor Cornell University MBA

I have had quite the non-linear path to my current position, but interestingly, everything I have done in my career up until this point has contributed to my present job. Beginning after graduating from college in pure math, I took a deep dive into the world of finance. I first worked in investment banking and then in equity research. The skills I acquired, while rather computational in nature, required more critical thinking and analysis when preparing presentations for clients or reviewing financial documents prior to public offerings—this is where my math major, with a grounding in the liberal arts, played a key role. In equity research, I focused on ecommerce stocks, and was immersed in equity capital markets—gathering insights from companies, industry, and market to craft reports that would inform investors. While these opportunities afforded me a great foundation in finance, I realized that I wanted to do more than report on companies’ highs and lows; I wanted to help increase the highs and mitigate the lows. I decided to go into consulting, and I needed an MBA to make this career switch. One of my favorite ways I’ve used my math major skills came during an interview for a fellowship for my MBA. In order to showcase leadership strength we were given a cooperative task: a rope was scattered all over the floor, and we were told to determine if the rope, when pulled on both ends, would create a knot or not. Immediately I thought, “Is this really happening?” You see, I had taken a course on knot theory in college and wrote my senior thesis on the topic. I was excited and terribly nervous about counting crossings and practicing visualization techniques I had not thought about in over five years. I finally decided that it was not a knot. We were divided into teams: those who said it was a knot (about eighteen people), and those who said 167

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it wasn’t (three people, including me). The team of eighteen declared that they had “three expert engineers” who could attest to it. My teammates said, with a smirk, that they had “an expert knot theorist.” We argued that it wasn’t a knot, and eventually persuaded everyone. As the facilitators pulled the ends of the rope, my stomach tightened, but at the last moment the faux knot loosened to show no knots. I received a Roy H. Park Leadership Fellowship from Cornell, a two-year full tuition fellowship. While I cannot say that this was the deciding factor in whether I received the fellowship, it certainly helped me to stand out in the crowd! While at Cornell, I interned with Accenture and worked with a large cable client. During my internship, I learned about Accenture’s higher education practice and found a home there full-time after graduating. A few years later, Comcast reached out with an opportunity to focus on strategy work, and I decided to make the change to my current position in Corporate Strategy at Comcast Corporation. In this role, I focus on the overall growth strategy of Comcast and NBCUniversal, with a concentration on business and geographic expansion and long-range strategic planning. Our team partners with business units across the organization to identify and execute strategic business opportunities, partnerships, alliances, and agreements. In particular, I have identified potential international opportunities for the company, analyzed the IP franchise origination and monetization process and timeline, conducted due diligence for prospective acquisitions, and worked with the Chief Financial Officer to construct a comprehensive consolidated view and accompanying analysis of our long-range strategic plan. My work environment is completely collaborative. We are project-based in our work, and create teams to tackle issues facing the company and industry. Our group works with other departments throughout the business, as well. While I may no longer be writing proofs or learning about different theorems, the characteristics of a degree in mathematics are embedded in all of my work: from calculating and analyzing the financial strength of different companies in varying industries, to creating logical arguments in presentations, all of these skill sets were developed when I was a math major. My degree in mathematics has always been a way to get my foot in the door. Whether it was with my first job out of college or during business school interviews, the math major is always a positive focus point for interviewers. When they see that I was a math major, there is a common understanding that this is a person who knows how to approach problems from multiple angles, undertake difficult analysis, and utilize critical thinking to come to solutions. They also know that this is oftentimes someone who will not back down from a challenge. Undertaking a math major is no small feat, and the grit that comes along with achieving one is widely recognized as a desirable trait.

Jacqueline Pfadt

Technical Lead Savantage Solution Ashland University BS Mathematics and Computer Science Lake Erie College MBA

I am a Technical Lead for a software development team working with our customers within the federal financial environment. Over my career, I have supported various federal agencies within the Department of Defense and the Department of Homeland Security. I initially got my job working with the Defense Finance and Accounting Service (DFAS) Agency as a civilian from an interview I did at a job fair at my university. The recruiters were looking for students with degrees in computer science, mathematics, and finance. I worked for DFAS for six years as an Information Technology (IT) Specialist. I then changed my role to the Project Management Office as a contractor, so that I was more directly involved in supporting application users. In my current role as a technical lead, a normal day involves a lot of collaboration with team members on our development team as well as with our clients. I have meetings to define business requirements, develop technical solutions for requirements, work with our partners throughout the software development life cycle, and support a production environment where users from various agencies use our software to post accounting transactions and do financial reporting. When I was an IT Specialist with DFAS, my role was more solitary, with periodic collaboration with the project management office for defining requirements and researching production issues. The solitary nature of my position was one of the reasons I changed my job to have a more collaborative role with the user community. Working more directly with the user community and leadership has 169

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increased the stress of my job, but has also resulted in many gratifying experiences and collaborative accomplishments. I have a double major in mathematics and computer science. My computer science degree has certainly helped me, but I have always said that it was my study of mathematics that has been instrumental to my career. The foundational skills I acquired to logically break down problems and solve proofs have equipped me with skills to break down business requirements/processes and complex issues in order to develop innovative solutions for our customers. Discrete Mathematics and Real Analysis were some of the courses that I feel have really benefited me. Using logic to define solid business rules for complex accounting and financial business processes to work within the standards and regulatory guidelines for the federal government have been essential in creating accurate solutions that account for all the different use cases in a complicated financial environment. My job has been extremely rewarding over the years, but it has taken a lot of effort to find work/life balance in a highly demanding environment. As I have progressed in my career, I have been able to find the balance to enjoy a successful career and family life. This is an important lesson that I think most professionals need to work at during various points throughout their career. Balance is essential for long term growth and sustainability. My biggest suggestion for those coming out of college is to be open minded to all sorts of opportunities. The foundational skills acquired from studying mathematics are broadly applicable and could prepare you for opportunities in areas that you would not necessarily expect. Getting involved in various groups that not just hone your mathematical skills but also your communication skills is very important. Being able to come up with solutions for complex problems is clearly a great asset, but being able to communicate those solutions to people at various levels in a professional organization is also important. The combination of these mathematical and communication skills creates a lot of opportunity for growth and success.

Ashley Pitlyk

Senior Data Scientist Care Otter Sam Houston State University BS Mathematics, Statistical Theory Minor Saint Louis University MA Mathematics PhD Mathematics

As a Senior Data Scientist at Care Otter, I use mathematics, statistics, computer programming (specifically, Python), a good helping of creativity, and LOTS of data to help improve healthcare for both the patients and their providers. On the consumer side, my team helps doctors use and visualize data in a whole new way that was previously only available to research doctors to enable superior patient care. On the development side, the data science team helps our developers come up with algorithms to do analytics faster and provide better results. This includes questions like, “How do you use algorithms to accurately and efficiently figure out if two patient records actually belong to the same person?” or “What’s the best way to create a spatial index?” I really enjoy my job because I face new and exciting challenges every day, and I know that conquering those challenges will make a difference in people’s lives. I also like that I’m given a lot of freedom in my job; I’m given a problem but not told how to approach it. How to approach it is left up to me, my creativity, and the current abilities of the cutting-edge technology to which I have access. Machine learning, fast computers, and tons of data? Yes, please! I was one of the first ten employees at Care Otter, and we’ve grown to over 40 people in the past year and a half. We began our company working in an ambulance bay converted to office space in the back of a hospital (which meant on nice days, we could open up the doors and enjoy some sunshine), but we have since moved to a bigger office to fit all our new people. Despite the move, we are still a very open and collaborative environment. Depending on the day, you might see a dog running around the office or some three-person chess or Loot Letter being played when we need to take a break. Care Otter is a very family friendly company. I get to work from home on Fridays, and my two year-old daughter, Emily, gets to see 171

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her mom doing cool stuff. I also enjoy getting to wear “nerdy” shirts, jeans, and my cowboy boots to work instead of dress shirts and slacks. Prior to working at Care Otter, I was an analyst at Booz Allen Hamilton doing data analytics and programming analysis tools and interactive data visualizations. Before that, I taught mathematics and statistics as a graduate student, and then as a professor at Mary Baldwin College. Teaching prepared me for explaining highly technical information to all audience levels in a manner that can easily be understood—a highly valuable skill in the job market these days. While I can’t say that I have used Fourier or harmonic analysis (my doctoral studies subjects) yet in my career, I can easily say the logic and problem solving skills from my mathematics background get used every day in what I do. I believe a background in mathematics, statistics, and computer programming is a great start for a rewarding, challenging, and fun career as a data scientist.

Kimberly Plesnicar

Actuarial Analyst II Zurich North America Dominican University BS Mathematics Roosevelt University MS Actuarial Science

In college, I was hesitant to declare my major. I had always really enjoyed my math courses, but I was unsure what type of career the degree could lead me to. I knew I wanted to work in an applied field, so I dabbled in accounting, business, and economics to see what struck my interest. Finally, one of my college professors suggested an actuarial career to me. I had never heard of an actuary and decided I wanted to learn more. I read several career books, researched the field and discovered it sounded like a perfect match: a career where I could use math and statistics on a daily basis within the business world. What sounded even more compelling to me was the fact that actuaries make predictions to protect insurance companies, businesses, and people from uncertainty. In order to better understand what this career would entail and prepare myself for the actuarial examination process for accreditation, I enrolled in a graduate school program that focused on actuarial science. While at school, I passed the first two actuarial exams and worked in a data analyst position, which provided real-world analytical skills in applications such as Excel and PowerPoint that would ultimately be very useful in my actuarial career. While completing my degree, I began working as an actuarial analyst at Zurich, where I have been for over four years. As an actuarial analyst, I employ different actuarial methods on a daily basis, which are both statistical and mathematical in nature. We often work individually on longer term projects, but collaborate and peer review to gain better insights. Depending on our roles, we also have the opportunity to communicate with the business about profitability, provide feedback and expertise to underwriters working in the field, and provide analyses that directly impact our balance sheets. 173

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The two main functions of an actuary include pricing and reserving. I have worked in both functions, and find them both incredibly interesting. Pricing focuses on how much we should charge our customers in order for the prices to be fair, competitive, and adequate to cover the risk we are assuming. Reserving ensures we are holding the right amount of money, or capital, in order to pay our customers’ claims and remain solvent. What I’ve discovered is that beyond the crucial analytical skills I obtained through my background in mathematics, communication skills are key. Oftentimes, actuaries have to explain relatively complex analyses to a broader audience and ensure that they not only understand the results, but what those results mean for them and what actions they should take as a result. There are also times when you will be working on multiple projects or spearheading your own, meaning project management skills are crucial. I’ve also found my coursework in programming to be quite useful in my career and wish I had taken more classes in that area. As you will discover, the examination process for becoming a credentialed actuary is very difficult. Depending on your career path, you will need to pass approximately ten exams, and it takes several years to complete them. However, many large companies that employ actuaries provide work-study time, study materials, and raises or bonuses for successfully passing an exam. Although I can attest it is not the easiest career path, I find actuarial science very fulfilling and interesting, and I would highly recommend it to anyone with similar interests.

Amanda Plunkett Analytic Team Lead Department of Defense Grand Valley State University BS Mathematics Western Michigan University MS Applied Mathematics University of Maryland, Baltimore County MS Statistics PhD Statistics

My mathematics training has opened many doors throughout my career. Currently, I lead a team of software developers and mathematicians within the Department of Defense (DoD). The team creates analytics which summarize large data sets, distilling useful information out of those data sets. Recently, the team has started working on recommender engines, which provide personalized suggestions (similar to Amazon and Netflix recommendations). The job is a good fit for me because I have the right skills to take a broad requirement from a user, such as “create a recommender that does x,” and determine the mathematical and statistical algorithms that need to be implemented behind the scenes. I found my first job after graduate school (MS, Applied Mathematics) before the days of LinkedIn by submitting my resume to INFORMS (Institute for Operations Research and Management Sciences). I was hired as a Modeling and Simulation Analyst, working for a DoD contractor, where I built simulation programs which helped military planners in their decision-making processes. I enjoyed this job, but after three years, found myself wanting a new challenge. Since the company was small, I decided to look elsewhere, which brought me to civilian work within the DoD. What drew me to the DoD was the fact that they hired a large number of mathematicians. I figured it must be a great place to work! When I began working for the DoD, I was hired as an intern within the Applied Mathematics Program. As an intern, I toured in six different offices, each for about nine months. This was great, because I was able to try different jobs to get a feel for what I enjoyed all while learning new skills in each office. Each tour was related to mathematics or statistics. Periodically, I would attend job-related math courses with the other interns in my graduating class. After three years we graduated from the intern program and joined a permanent office of our choice. 175

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Things that I like most about my job are: 1) Time flexibility. I am required to work 80 hours per two weeks, but have the flexibility of when I want to work. If I work more than 80 hours, this time can be saved up as “credit hours” to be used at a later time. This provides a great work-life balance. 2) Job flexibility. Due to the fact that the DoD is large, if I decide that I am ready for a new challenge, I can find a new position without having to change employers. 3) Travel. I’ve had the opportunity to travel to three different countries as part of my official duties. In one situation, my assignment was in England for three months, which provided me with the opportunity to travel to other European countries in my free time. 4) Education. My MS and PhD degrees in statistics were sponsored through available education programs. This is in addition to learning via on-thejob training, conference opportunities, and seminars/classes available within the DoD. 5) Smart colleagues. I’ve met many smart mathematicians and statisticians during my time at the DoD, which has raised my skill level.

Elizabeth Pontius

Attending Physician Emergency Department MedStar Washington Hospital Center Assistant Professor of Emergency Medicine Georgetown University School of Medicine Wellesley College BA Mathematics Baylor College of Medicine MD Medicine

I am a senior attending physician in the Emergency Department at MedStar Washington Hospital Center, a Level I Trauma Center in Washington, D.C. In addition to my clinical responsibilities, I also teach medical students and emergency medicine residents about emergency bedside ultrasound and its utility in the Emergency Department. When I went to college, I thought I wanted to be a physician, but I enjoyed the analytical thinking required for my mathematics classes in high school. I studied both subjects, but when I studied abroad in mathematics, though I enjoyed the mathematics coursework, I missed my science classes and learning about the human body. My decision to become a physician was cemented. I happened upon Emergency Medicine during my surgical clinical rotation in my third year of medical school, and fell in love with the fast pace, diagnostic dilemmas, and camaraderie of the staff. A typical day for me involves direct patient care in the Emergency Department. On average, I see about 18 to 20 patients in an 8-hour shift, but that number can climb up to 35 or 40 on a particularly busy Fast Track shift. I work in concert with nurses, technicians, respiratory therapists, as well as medical students and resident physicians (physicians in training, who are learning to be emergency physicians) to help things flow smoothly. I also collaborate with patients’ primary care physicians, consultants, admitting physicians, and social workers to plan the best course of action for every patient I see. 177

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My coursework in mathematics provided me with a framework for how to critically but quickly analyze a problem, an important skill in Emergency Medicine. Every shift, every patient, is different in the Emergency Department. Some patients are critically ill or injured and need obvious immediate intervention, while others may take more time and thought to figure out how to proceed. In the busy department where I work, I also have to be cognizant of which patients are in the waiting room, awaiting an evaluation by a physician. Having a global picture of what is happening in the department allows me to rapidly assess which patients need my immediate attention, which patients can wait, and what tests I can order to aide the evaluation of all of them. I also have advanced training in emergency ultrasound. It would be impossible to understand how an ultrasound image is created without first understanding the physics behind the machine – and to understand physics you need to understand mathematics. My coursework in both allows me to manipulate and optimize the images I obtain, which provide important information to other physicians involved in the patient’s care. It seems a long way from calculus or combinatorics, but the analytical thinking learned as a mathematics major is a skill many physicians have to develop after medical school, but I had already learned.

Emilie Purvine

Data Scientist Pacific Northwest National Laboratory University of Wisconsin–Madison BS Mathematics Rutgers University PhD Mathematics

I do applied mathematics (graph theory and algebraic topology) for applications including cyber security, power grid, and information science. But as a scientist at a national laboratory, my job entails much more than just the research. I get to interface with government sponsors to identify problems that they have where I can make a difference. I manage projects which include mathematicians, domain experts, and software engineers. And I also get to do the fun stuff: real math that makes a difference in a tangible way. As a graduate student I took a fellowship from the Department of Homeland Security. One of the requirements of that fellowship was to intern at a national laboratory. There was already a connection between Rutgers and PNNL, so I went to work there for a summer. The research was engaging and exciting, so I went back the following two summers as an intern and was offered a postdoc when I graduated. I worked very hard as a postdoc and after a year and a half they hired me on as a staff scientist. At a national laboratory there isn’t really a “normal day,” but I can report elements that could be part of any of my days. There are the meetings—progress meetings where we report what we have been working on since the last meeting, or collaborative meetings where we discuss ideas for future work. Some meetings can be productive and exciting, whereas others are a mere necessity to move things along. On days that I don’t have meetings, or not very many, I get to fill my day with research or management. The research days are much like you would imagine: reading papers, thinking about concepts, writing code to test hypotheses, and talking with others to get ideas. These are the fun days where I really get to see how my ideas work. Management tasks include building presentations for external 179

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sponsors (the folks that fund us to do our research) and budgeting for projects I manage. Finally, there are travel days. Travel to conferences to present work and build collaborations, or travel to sponsors to brief them on my work. The environment at PNNL is very collaborative. I wouldn’t be able to work on cyber security, power grid, and information science without the help of many others. With a degree in mathematics I knew almost nothing about the power grid. This is where I rely on other experts to educate me on the major questions so that I can do the algorithm development and research that I do best. I also work with other mathematicians that know different areas than I do. Nobody can be an expert at everything, so I rely heavily on my network to solve the types of complex problems that we tackle at a national laboratory. As I mentioned before, it was really my fellowship and the connections between my graduate university and PNNL that helped me find my particular job. But being in the field of mathematics allowed me to attend many conferences over the years and meet people from all different career paths – academia, industry, and government. From talking with many of them, I decided that the best fit for me and my goals was government, and specifically a national laboratory. My degree in mathematics helps me every day. I am first and foremost a mathematician at a national laboratory. I prove theorems and discover new applications of previously developed algorithms. In all of my projects, I take real world data or structures and turn them into mathematical structures. I then study the mathematical properties of these structures in order to gain insight into the application space. For example, a power grid can be thought of as a graph where power generators are vertices and power lines are edges. Understanding the shape of this graph can help us in building a future power grid that is resilient to large failures while keeping costs low. Balance can be tricky, especially if you are in high demand on many projects. But there are ways to create boundaries. For example, don’t work on weekends or turn off email on your phone after a certain time of day. It’s easier to say than to do, but, as long as you discuss these boundaries with your managers, it can be done. Make sure you know what deadlines you need to hit, and hit them. Sometimes that will require breaking these boundaries, but don’t let it persist. Always make sure that breaking down these boundaries is a short term event, not long term. Two pieces of advice: (1) learn to code. Coding is an essential part of what I do. I cannot just develop algorithms on paper, I need to make sure that they work. I do not do large-scale development, only prototyping, but I need to know how to work with developers to produce a large-scale robust implementation in the long run. Just knowing the basics (how to program basic algorithms in Python, for example) will go a long way in both prototype development and communication with software developers. And (2) do an internship. It’s difficult to know what it’s like at a national laboratory without getting your feet wet. All labs offer internship opportunities at all levels – high school, undergraduate, and graduate students. Just poke around a few websites and you’ll find them!

Gregory Rae

Producer and General Manager Martian Entertainment Harvey Mudd College BS Computer Science and Mathematics Manhattanville College Doctor of Humane Letters, Honoris Causa

My career path, at first glance, appears to be anything but straight. After graduating from college, I worked as a software engineer at Google, then on political campaigns, before ending up in a career producing theater. While these look dissimilar, in each experience an important part of my work involved telling stories. As a software engineer, I was in charge of log analysis at Google. A significant part of my job was to look at very large data sets and extract interesting information from them. The most interesting data are those that are anomalous, and figuring out why the data looks weird requires constructing a story to describe why. A dip in midday traffic that only occurs in some countries? Perhaps that is explained by the fact that Spain has a tradition of siestas, and in France they actually take a break for lunch, while the United States does not. These analytical skills translated well into the realm of politics. On my first political campaign, one of my daily duties was to predict our daily donations. Having the experience of looking at time series data and describing not only what would likely happen in the near future, but also describing how current events could shift them, was instrumental in deciding where to focus fund-raising efforts. It was an act of political activism that introduced me to producing theater in the first place, but it is my belief in the power of telling stories that keeps me doing it. In 2011, I got involved as a producer of the Broadway play The Normal Heart, because I felt that a generation of people did not know the impact that HIV and 181

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AIDS had during its onset in the early 1980s. We won the Tony Award that year (my first of four), which inspired me to continue producing theater. My role as a producer varies from project to project. Sometimes it is limited to raising money and working on marketing the project (where a robust knowledge of ticket sales analysis and how to analyze demographics comes in quite handy). But it can also require working with the creative team on the script and designs, making casting decisions, and overseeing every aspect of the show. As a general manager, I help other producers budget their shows, comply with union rules, and make sure the show is running smoothly. In any case, before signing on to a project, I need to look at whether it’s feasible to have a solid run. Knowing the relationship between the budget numbers and being able to evaluate the assumptions for a recoupment schedule are key to this process. My experience studying logic, proof, and computer programming inform my approach to constructing a story. Having rigorous training in breaking down a problem into its constituent parts, solving those simpler problems, and combining the answers into a solution to the larger problem is a skill that applies to any field. Including storytelling.

Rachel Ramirez

Actuarial Analyst National Life Group Texas Christian University BA Mathematics with Actuarial Science Concentration, Economics Minor

I have always enjoyed math and made the realization in my senior year of high school that I wanted to go to college for it. The problem was, however, that I really wasn’t sure what I would do with my math degree. Luckily, I had an older cousin who was in the actuarial field, and he was able to introduce me to it. I then switched my major soon after starting college to a math degree with an actuarial concentration. Just to give a little background, the Investopedia definition of an actuary is the following: An Actuary is a professional who assesses and manages the risks of financial investments, insurance policies, and other potentially risky ventures. This is just one of many descriptions of the profession. Another one I like even better describes actuaries as part super-hero, part fortune-teller, part trusted advisor. There are so many different types of opportunities within the actuarial science field, there is really something for everyone. To give some background on myself, I am an actuarial analyst at a life insurance and annuity company called National Life Group. I am working towards earning my ASA (Associate of Society of Actuaries) designation. This requires me to work full time, and also pass at least six rigorous exams. I applied for an internship with National Life Group before my final semester of college. I fortunately was hired as an intern and moved on to full time after I graduated. The culture of my company is outstanding and provides a fun and developmental work environment. I won’t lie though; a normal day is mostly spent behind a computer. However, as far as the specifics of my day go, it can be different each day, which is nice. At my 183

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company we have an actuarial rotational program that allows actuarial students to gain exposure to different departments within the actuarial area. During my first rotation the environment was very collaborative, which I enjoyed. In my new rotation, the environment is more solitary, but I still communicate frequently with team members and others in the company. Since I chose the actuarial path in college, I was able to take classes that prepared me for the first two preliminary actuarial exams. I was able to pass both of those before getting out of college, which definitely helped me land my internship and my full-time job. When seeking a job in the actuarial field, it definitely helps to have a couple of exams passed when applying for a full-time job (or internship even). The field is growing more competitive and well-known. Going through the rigor of a mathematics degree helped me develop and strengthen my problem-solving and analytic abilities. These are crucial qualities to have as an actuary. College also helped me by preparing me for the first two exams, so that meant fewer exams I had to take while working a full-time job. Juggling the exams and a full-time job (and also personal time) can be challenging. During my first rotation, I was on the Product Implementation team within the actuarial area. My job on this team was mostly to validate our illustration system (a system managed by a third party vendor that allows the illustration of many different scenarios on an annuity or life insurance policy). If our internal Excel validation tool (built and maintained by my team) did not match our online system’s results, we then had to rely on problem solving and analysis to figure out what the problem was and remedy it. Although our tools do most of the calculating for us, knowledge of certain mathematical principles were helpful in “debugging” cases that were especially problematic. This career path can be challenging, especially with the extra effort it takes to study and pass exams after college, while having a job. However, most actuarial programs (my company included) offer great paid study time for studying actuaries. This makes the test taking more manageable and successful. My advice to students who are interested in this field is to stay dedicated, stay focused, pass exams, and be sure to have some fun along the way!

Blake Rector

Director of Analytics Powin Energy Cal Poly, San Luis Obispo BS Mathematics California State University, Long Beach MS Mathematics Portland State University PhD Mathematics

I am the Director of Analytics at Powin Energy, a company that manufactures and operates grid-scale battery storage systems. These systems are typically the size of medium-sized warehouses. A “small” system may have the capacity to supply the equivalent of one-thousand homes with power for one hour, and a “large” system may be able to supply twenty-thousand homes with power for four hours. As the Director of Analytics, my time is generally split into three categories: (1) I manage the energy market participation for the battery systems we operate. This includes applying optimization methods to maximize revenue, understanding the rules for market participation, assessing market performance, validating financial statements, and coordinating with the operations team in real-time. (2) I develop new algorithms for future projects. This involves software architecture, careful documentation and working with software developers. (3) I pursue business development through conversations with potential clients, explaining the value of energy storage in their use cases. My work days vary quite a bit depending on the real-time operational status of the systems and the immediate needs of the business development team. If there are real-time operational issues, then I am coordinating with many groups of people and making sure that everyone has the information they need to keep the systems online. In the business development work, I am trying to engage in conversations with potential customers to learn about their needs and help them understand the value of Powin battery storage systems. If there are no other urgent needs, then I get to think more deeply about algorithm design. When I work on the mathematics within the algorithms, I am deeply solitary. My training in mathematics helps me find elegant ways to solve complex problems, and the optimization of the energy storage problem is data-rich and difficult. To solve it, one must model revenue from providing various market services and 185

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determine which combination of services will earn the most revenue over the course of the day. This is done by defining the objective function and constraints, in a way that respects the market rules and system parameters, and applying numerical methods to find the solution. Once you find a line of work or a vein of research or a type of mathematics that fits with your personality, seize it and do not let go. Focus your attention on one or two opportunities and pursue them deeply. No matter what you are doing, whether you like it or not, the best possible outcomes happen when you do a really good job at what you are doing now.

Mary Lynn Reed

Chief, Mathematics Research Group National Security Agency Georgia Institute of Technology BS Applied Mathematics University of Illinois Urbana-Champaign MS Mathematics PhD Mathematics University of Maryland MFA Creative Writing

As Chief, Mathematics Research Group at NSA, I lead an organization of mathematicians, cryptographers, statisticians, and engineers, who perform mathematics and cryptography research and cryptographic design, and apply advanced techniques from mathematics-related fields to create breakthroughs in cryptology, information processing, signals intelligence, information assurance, and cybersecurity. I started at NSA as an Applied Research Mathematician. I spent the majority of my career performing research and development on a variety of mathematicallyoriented NSA mission problems, focusing primarily on large-scale data analysis, cryptanalysis, statistical methods, and high-performance computing. Over the years, I also found myself gravitating towards leadership, first by leading projects, then teams, and now, a large organization with a substantial research portfolio. There is no “normal” day in my current job. High-level management at NSA is many things, but it’s never boring! My favorite activities include attending research seminars or project updates by mathematicians or cryptographers in my organization or one of our contract affiliates, and also mentoring our junior employees and emerging leaders. Having a positive impact on someone else’s career can be very rewarding. Other common activities in my job include representing my organization at high-level leadership and strategy meetings, giving briefings across NSA and the broader Intelligence Community, keeping up-to-date on emerging and sustained mission priorities, and setting the strategic vision for Mathematics Research at NSA in response to those mission needs. 187

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The work environment at NSA is highly collaborative. Our mission problems require the coordination and collaboration of large interdisciplinary teams. Throughout my career, I have worked just as closely with intelligence analysts, computer scientists, engineers, and policy experts as I have with other mathematicians. My degrees in mathematics were critical in obtaining my job at NSA. Although I pursued my PhD with the intention of a career in academia and teaching, I encountered NSA during my initial academic job search and became intrigued by the opportunity to apply mathematics to the service of my country. Although I still love to teach and could see myself returning to a faculty role someday, I’ve done things at NSA I literally couldn’t have done anywhere else, and it’s been an extremely rewarding experience! I have heavily leveraged both my statistics and applied math background from my undergraduate degree at Georgia Tech and my advanced abstract algebra knowledge from my PhD work at Illinois throughout my career at NSA. I’ve worked projects in elliptic curve cryptography, coding theory, graph theory, and statistical analysis. I’ve also made heavy use of my early studies in computer science (I started out as a CS major at Georgia Tech), in projects that involved understanding assembly language and machine architectures, as well as optimizing code for high-performance computing environments. The diversity of projects for mathematicians at NSA is amazing. Finite fields, Fourier series, and access to some of the best computers in the world. We’ve got it all! Regarding work-life balance: NSA is a great place for mathematicians who want a healthy work-life balance. For most of my career I’ve worked a standard 40-hour work week with very flexible hours. However, truth in advertising, my current job as Chief, Mathematics Research is a bit more demanding than that. My time is often over-booked with meetings during the regular work days, so I’m occasionally in my office in the evening or sometimes on weekends. But even at the highest level of leadership at NSA, there is respect for work-life balance, and leaders try to keep each other on track to take time off and ensure we have the breaks we all need to be effective in our jobs and happy in our lives. If you’d like to be Chief, Mathematics Research at NSA, I’d say it’s useful to have broad interests in mathematics and related fields, as well as a commitment to the development of a strong technical workforce. It’s a high honor to be in the position of representing such a talented group of mathematicians and cryptographers working so hard for our nation’s security. There’s no particular area of specialty I’d recommend you study to have my job, but the ability to quickly come up to speed on a new mathematically-oriented topic and also the ability to work well with others (at all levels) are both essential.

Adam L. Rich

Actuary Head of Specialty Lines Analytics Beazley Group PLC Brigham Young University BS Mathematics Fellow of the Casualty Actuarial Society

I am a pricing actuary for an insurance company called Beazley. Beazley is a small company that focuses on what are called “specialty lines” of insurance. We insure things like businesses who provide professional services, sporting events, companies (against cyberattacks), large construction projects, and environmental cleanups, to name a few. My primary job is to help the people who sell our insurance, called underwriters, know what they should be charging. I also supervise the other actuaries on the Specialty Lines Analytics team. As an actuary, I do use mathematics on a daily basis. I’m not always using the math that I learned in college, but my degree in mathematics prepared me for this career, especially the focus on logical thinking and problem solving. In addition to math, actuaries also need to have good communication and business skills. It is necessary to have strong computer skills, too. When I was in college, I originally wanted to be a teacher. During my senior year, however, I decided that I wanted to work for a few years before going to graduate school and sort of stumbled into a position with a small company in NYC. I literally got a job as an actuarial assistant by answering an ad in the paper! I didn’t have any actuarial exams when I applied, but they took a chance on me, and I am very glad they did. I changed positions and companies every few years while taking my exams before finding my way to Beazley, where I have been since 2011. I became a fellow of the Casualty Actuarial Society in 2012. 189

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Taking the actuarial exams can be an arduous process. It has been compared to being in graduate school part time, although you mostly are studying on your own and not in a classroom setting. The first few exams focus on financial mathematics, probability, statistics and model building. After that, depending on the type of actuarial work you are preparing for, the exams focus on how actuarial mathematics is actually applied in the business world. For me, taking the actuarial exams has been a rewarding alternative to graduate school. I’ve been able to comfortably support my family while still continuing my education. Passing the exams and becoming qualified is also very rewarding in opening new opportunities and preparing you for more challenging, visible, and exciting work. For example, because of the specialist nature of the business at Beazley, we have had to develop different methods for monitoring how our claims develop. I’ve been able to work with the claims management team to come up with a simulation model for aggregate performance of different products. The claims managers focus on the claims with a lot of uncertainty and provide me with different possible outcomes and associated probabilities. The model I built then calculates thousands of combinations of these different scenarios to give them a range of possible outcomes. It also adds in provisions for things we don’t know about yet and the possibility that they are making projections using limited information. As my career in actuarial science has progressed, I’ve learned that there is really no such thing as a normal day. The actuarial exams give one such a breadth of knowledge in so many areas of insurance operations that actuaries are expected to be able to contribute in a variety of problems, some that are not really mathematically complicated. Even as my responsibilities and involvement have increased, however, I still find that the profession maintains a flexible work/life balance. It is very rare that I work more than 45 hours per week, most weeks I work about 40. I work for an international company so I do travel but not all actuaries are required to do so. My employer understands that I have obligations outside of work and is accommodating when needed. If you think this kind of work is interesting, I would recommend you take some steps while in college to prepare. Take the first and second actuarial exams on your own. This will show your future employer that you are serious about the profession and that you can study in addition to your other responsibilities. Take classes outside of math in areas that interest you. If your school has an actuarial science program I would recommend maybe minoring in that discipline but majoring in math. Good luck!

Christina Roberts

Assistant Vice President Senior Catastrophe Modeling Analyst Validus Reinsurance St. Olaf College BA Mathematics and Spanish

I really didn’t know what I wanted to do with my math major when I graduated. In search of guidance, I attended the monthly colloquia hosted by the St. Olaf math department, and someone came to speak about catastrophe modeling. I thought it sounded interesting, so I attended the Minnesota private college job fair where I spoke with a couple of companies that were offering a position in that field. I started working for a reinsurance broker immediately after graduating. After eight years, I moved to the reinsurance side, where we provide insurance for insurance companies. As part of the catastrophe modeling department, my general role is to provide our underwriters with the analytics they need to decide whether we want to do business with specific insurance companies. We are reinsuring hundreds of different companies by taking a sliver of various sizes of each insurance company’s reinsurance purchase, specifically as it relates to natural or manmade disasters (hurricane, earthquake, tornado, terrorism, etc.). In order to have a profitable portfolio, we need to provide our underwriters with analytical insights, which we do by digging into the insurance company’s exposure data to review the quality, accuracy, and risk. We then use both internal and licensed third party catastrophe models to come up with loss metrics, e.g. probability distributions of loss. These metrics help us determine the likelihood of a disaster impacting each insurance company and therefore our aggregated portfolio. In conjunction with that, we work directly with our research team, who are on the forefront of the newest scientific findings, in order to adjust the standard output as determined by the models. While much time is spent digging into the data, a large part of my role is to communicate the results effectively to both internal and external stakeholders 191

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to help them make business decisions. It’s all about problem solving. We have some pieces of the puzzle, and our job is to pull everything together to build that story, which includes determining what is and what is not important. My degree in math provides me the background to think analytically and critically and to understand when results that come from the model don’t make sense. In addition to the modeling of client portfolios (our core business) we also spend a significant amount of time working on ad hoc projects ranging from finding innovative ways of looking at data, improving the efficiency of our processes, incorporating “big data” technology into our workflow to be harnessed through programs like SQL, R, and Python, and exploring emerging insurance markets such as cyber insurance. I value the culture I find at my job which allows me independence when I want, but also provides me resources when I’m working on a collaborative project. I find that it is a perfect mix between heads down work and working in a group setting. What I also value is that no two days are the same. There is always something new to do and more to learn, both from the expansion of the industry and from colleagues bringing in new lines of thinking. I am surrounded by really smart people who help push the whole group towards excellence. If I were to go back to give myself a leg up in this industry, I would have spent more time learning about coding and data manipulation. The industry is moving towards using big data to help support underwriter decisions. Having skill sets to manipulate data opens lots of opportunities. I also think that it is crucial to be able to communicate effectively. Your analytical insights are only as good as your ability to explain them to less technically experienced stakeholders. The analysts most successful in this role have a good balance between analytical thinking and communication and are willing to work hard to solve problems.

Shannon Rogers

Curriculum Developer Art of Problem Solving University of California, Los Angeles BS Mathematics

After deciding to pursue a math major at UCLA, the California Teach Program provided an opportunity to work in the elementary school on campus, the UCLA Lab School. It was there I realized I particularly enjoyed working with elementary students. This led to my seeking a job teaching the elementary group of the Los Angeles Math Circle (LAMC). Both the California Teach Program and LAMC I discovered simply by being on the Math Department’s email list. As graduation neared, LAMC director Olga Radko connected me to AoPS CEO Richard Rusczyk, as he was looking for staff to help develop their new elementary school math curriculum. For nearly seven years now, I have been writing Art of Problem Solving’s (AoPS) elementary math curriculum, Beast Academy, as well as working with the AoPS Online School in a variety of roles! Starting at a relatively small (and growing) company, I have had an exciting opportunity to be involved in a lot of different projects that span nearly all parts of the company, including helping to write lessons for our most recent expansion into in-person learning centers with AoPS Academy. There isn’t quite a normal day at AoPS, and I love that! I’m fortunate to have responsibilities that are an interesting mix of long-term projects and more immediate day-to-day tasks that can arise as part of running online courses. As each project nears completion, there are always new projects that come up or improvements to make on prior projects. My work environment is highly collaborative. The work spaces are groups of us in large rooms with few walls. Every project requires multiple hands on deck, so, whether it’s a team of curriculum writers working on lessons or a team of developers designing and implementing a new feature of our website, I’m constantly collaborating with the people around me. 193

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Writing math curricula definitely keeps those basic math skills sharp, and working on Beast Academy helped me explore elementary school math on a whole new level. My experience with Math Circles (and recreational math) was invaluable in thinking about new and different ways to present “standard” material, and in developing lessons on deeper and more rigorous topics that students might not see in other elementary math curricula, but that they can explore with just some basic arithmetic skills. Math is also a community experience here: we have extensive discussions about the way we understand particular topics, how students understand certain topics, and how we can continue to improve our curriculum. We’ll compare and contrast which of us came up with the most interesting way to solve a problem from a recent math contest. Whether we’re writing or solving problems, working with students on their homework, or testing out the most recent puzzle from our colleague and World Puzzle Champion Palmer Mebane, math is all around here. Also, the logic, perseverance, and problem-solving that comes along with the study of math has paid off far beyond the content knowledge, as we develop new features, tools, and more efficient methods to accomplish some tasks, or as we think creatively to tackle new challenges that arise as AoPS continues to expand. The job description I saw from AoPS surprised me with how much it matched my career interests in a more precise way than anything else I’d ever seen before. Just because you don’t know a job exists doesn’t mean that it doesn’t, and the right employer might even be willing to evolve a job around your skills and interests. I was incredibly lucky to find AoPS, where I’ve been able to work on a lot of projects that made use of many of my talents beyond those that fulfilled the initial job description. I’d encourage anyone studying math to keep their other interests and skills in mind; a background in mathematics can be applied in so many different ways to so many opportunities. Seek out and try things that seem interesting; talk to people already working in areas you might like to enter. Where you end up might surprise you! I also encourage anyone even vaguely interested in recreational math or teaching to look into Math Circles (both student and teacher groups). My involvement with this community has provided constant encounters with new and interesting math, and I am continually encouraged and inspired to improve my skills with teaching, with math, and with teaching math.

Lucas Sabalka

Computer Vision Specialist Ocuvera, LLC University of Nebraska–Lincoln BS Mathematics, Computer Science, and History University of Illinois Urbana-Champaign PhD Mathematics

I am a Computer Vision Specialist. I work for a company called Ocuvera that specializes in reducing the risk of patients falling in hospitals. Falls can lead to serious injury or even death and are very expensive for patients, insurance companies, and hospitals. We place cameras that record in three dimensions in hospital rooms, and write algorithms to have computers automatically monitor patient behavior. If the algorithms detect patient behavior that elevates their risk of falling, the system automatically notifies nurses so they can assist the patient. I am part of a team of three mathematicians who write the algorithms that perform the automatic monitoring. To give an idea of what I do, here is one of the problems that I have worked on. Consider a video of a hospital room. The room may be cluttered with a chair, a hospital table, medical equipment, and perhaps a nurse or visitor to a patient, but it always has a hospital bed. Based on this image, we identify where the bed is in three dimensions, modeling the height of the bed, its position in the room, and whether the head of the bed is raised. That by itself is a complicated and delicate problem: how do you take a depth image, with no other information, and reliably instruct a computer to interpret this set of pixels as representing the bed, and extract a 3-dimensional model from it? Once a model is found, how do you determine whether or not it is a “good” model based on the data? If the patient raises the head of their bed, how do you update the model in real time to reflect that movement? I came to Ocuvera in a roundabout way. I got my PhD in geometric group theory. I had planned to be a research professor of mathematics, and worked hard 195

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on publishing research papers, attending conferences, teaching, and contributing to my universities. I took a postdoctoral research fellowship at the University of California, Davis, and another at Binghamton University in New York. My research was always theoretical, but during my postdocs I began consulting on more applied problems and projects. One of those projects was for a computer vision project making an automated physical therapy monitor for a company related to Ocuvera in my home town of Lincoln, Nebraska. After finishing my postdocs, I got a tenuretrack research position at Saint Louis University. However, while we liked the university, my wife and I decided to move back to our hometown. When I got the offer to work for Ocuvera, it was a difficult decision to leave academia, but after the academic year was up, I made the transition to industry. At Ocuvera, my normal work day is pretty flexible. About half of my day is working with other people, and half of my day is working alone. We have a short daily progress meeting, and various weekly meetings on different aspects of our project. It is a small business, so everyone wears multiple hats. I, for example, oversee writing and implementing our government grants, work with our deployment team to execute studies of our product, and work with hardware manufacturers to secure the cameras we need, in addition to my main duties of working on computer vision. Working on computer vision involves collaborating and brainstorming with my colleagues, thinking about the best way to solve various problems, and implementing those solutions in code. Computer vision does not necessarily require a degree in mathematics, but it does require a solid understanding of many mathematical topics. Some of the topics I have used in my job at Ocuvera include: geometry, probability theory, statistics, calculus, graph theory, matrix theory, and complex analysis. My degree in mathematics shows that I can understand advanced topics, that I am a quick learner, and that I am a good problem solver. Though my background in computer science helped, I got my position because of my mathematical background and problem solving ability. My advice to mathematics students considering their future career is to remember that there are industry positions available to mathematicians. Think about what industry positions you might enjoy, and consider taking basic courses in important areas. For computer programming, it is not important to have a degree in software architecture, but having some exposure to programming languages is a benefit. I also highly recommend seeking an internship or short-term job at a company that could be a good fit for you: you gain familiarity with whether you would enjoy that field, you gain useful experience for your curriculum vita or resume, and often those temporary positions can turn into a full-time job offer.

Jeffrey Saltzman

Proprietor Cottonwood Applied Mathematics University of Wisconsin, Madison BA Applied Mathematics, Engineering, and Physics New York University MS Mathematics PhD Mathematics

My interest in mathematics surely started when I was in 7th grade. My teacher, who preferred to go by Mrs. Collier even though she had a PhD, organized and advised a math breakfast club. We learned about logarithms, geometry, and even a bit of trigonometry along with applications. Mrs. Collier introduced the topics in such a fun and memorable way that I never lost interest in mathematics. My father, an electrical engineer by training, showed me how Ohm’s law was applied in many electrical and electronic circuits. In high school, math served as a helpful entry into some of the quantitative sciences, such as physics and chemistry. When I went off to college I could not decide whether to study engineering, physics or mathematics. I was gratified to find at UWM I could study all three disciplines within their AMEP (Applied Mathematics, Engineering and Physics) program. While at Wisconsin I took courses in programming and numerical analysis. I was enchanted by the latter. It was exciting understanding the use of mathematical theory and computing to solve problems to an arbitrary degree of accuracy otherwise unsolvable by pencil and paper. This same enchantment led me to graduate school, where I pursued degrees in mathematical and numerical analysis. Through some serendipitous events coupled with some very thoughtful advice from my thesis advisor, Jeremiah (Jerry) Brackbill, I finished my PhD and started my career at Los Alamos National Laboratory (LANL) in New Mexico. For the next 18 years I worked in both defense and energy programs at LANL. In that time I served as a staff scientist, team leader, deputy group leader, and group 197

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leader. During this period I had the opportunity to work on some of the largest computers in the world, developing numerical algorithms for large simulations as well as working within teams to ensure large multiphysics codes provide stable and accurate results. Moore’s law and the changing funding emphasis within the government ensured I was always learning exciting new science and engineering. In addition, it was nice to see my work and the work of my colleagues carried out in the energy and defense policies and strategies of the United States. Later in my tenure I became involved with proposal, project, and people development and management. I never took advantage of business and/or finance course offerings in college, as I had not anticipated having to develop these essential management skills. As a result, I made it my responsibility to ensure my employees had the time and resources to fully develop the necessary knowledge and skills. Through a few more serendipitous events, my career shifted from government to industry. I was invited to build an applied mathematics department at Merck Pharmaceuticals. Later, I took the role of project manager for the Predictive Sciences initiative at AstraZeneca. Making the transition to the pharmaceutical/biotech industry was simply the most intense period in my life. I had tremendous knowledge gaps in human biology and biochemistry to fill while trying to understand, navigate and deliver a relevant applied mathematics department within a large multinational corporation. Critical knowledge is also a moving target, as technologies within the industry completely change – seemingly on a three-year basis. I had never learned so much so quickly, nor could I have ever anticipated the research challenges and data/information/knowledge deficits faced by this industry. It was a remarkable experience to be part of companies and programs developing life-saving and/or life-enhancing drugs. After retiring from AstraZeneca, I have entered into a third phase of my career as an independent consultant. The business strategy and tactics for this concern are under development but I can predict new challenges and opportunities for learning. At the risk of being pedantic, I can point out several common threads throughout my career so far. Although a clich´e, change is indeed a constant. As a result, continuous learning of science, business, and people skills – even if you are not going to be a manager – is critically important. Finally, I have learned in a very practical way mathematics can and does make a difference. Today, more than any time before, a quantitative outlook is truly valued in industry and government.

Bonita V. Saunders

Mathematician National Institute of Standards and Technology College of William and Mary BA Mathematics University of Virginia MS Mathematics Old Dominion University PhD Computational and Applied Mathematics

The variety of jobs I’ve held gives me a unique appreciation for the power of degrees in mathematics and related fields. I’ve taught mathematics and computer science at two Historically Black Colleges and Universities: Norfolk State University and Hampton University – and worked as a programmer analyst at a private company before landing my current position as a research mathematician at the National Institute of Standards and Technology (NIST). NIST is a US government agency that conducts theoretical and applied research to advance scientific technology and improve measurement standards to strengthen the competitiveness of US industries in the international marketplace. I am a member of the Applied and Computational Mathematics Division in the Information Technology Laboratory, one of several research laboratories at NIST. Members of my division consult and collaborate with other NIST scientists while also conducting research in their own areas of expertise. The broad mission of NIST provides flexibility for the development of projects. Ideally, you try to either create or join a project where your own research interests gel with the project’s NIST-supported goals. Such was the case when I joined the NIST Digital Library of Mathematical Functions (DLMF) Project, a massive undertaking to update and expand the National Bureau of Standards (NBS) Handbook of Mathematical Functions first published in 1964. The handbook contains definitions, formulas, and tables for all types of mathematical functions ranging from the elementary exponential and trigonometric functions to special functions such as Legendre, Bessel, and Airy that solve problems arising in the mathematical and physical sciences. The new project (DLMF) focused on the development of a freely available online resource, available at dlmf.nist.gov, as well as a new printed publication. 199

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As I searched for the best way to support the DLMF Project, I discovered that my PhD research in grid generation could be used to help plot accurate graphs of complex function surfaces. While a graduate student at Old Dominion University I had studied grid generation with an aeronautical engineer at NASA Langley Research Center in Hampton, Virginia. When an engineer designs an airplane wing, he or she must solve equations that model the air flow over the wing to determine the best wing shape. Since these complicated equations must be solved at many points around the wing, the calculations must be done on a computer, and the points must be chosen carefully so that the engineer receives an accurate picture of how fast and smoothly the air flows. The points make up what is called a grid, or mesh. Grid generation is the development of computer codes that pick the optimal location for the mesh points. It is used in any area of research – such as aerodynamics (airplane, automobile design), hydrodynamics (ship design), electromagnetics, and materials science – where equations must be solved over an oddly shaped domain. While considering the problem of developing graphs and interactive visualizations of function surfaces for the project, I realized that I could generate grids that would allow me to easily plot function surfaces defined over oddly-shaped domains where there were branch cuts, zeros, poles (points where the function diverges to infinity), or other areas of interest. Eventually I created a sub-project of the DLMF Project supported by a dedicated team of computer scientists, mathematicians and college students. We designed and created more than 600 graphs and interactive visualizations of functions for the DLMF. More than a decade of work led to numerous technical publications and talks, including more than fifteen presentations at international conferences in nine countries. Also, along with the other NIST members of the DLMF Project team, I received a Gold Medal, the highest honor awarded by the US Department of Commerce. I have found NIST to be a wonderful place to work, but it can also be a little intimidating, especially for freshly minted PhDs just starting out. It’s important not to isolate yourself, but to get to know others in your division and other laboratories at NIST. Carving out time to keep abreast of your research is definitely important, but you should also be open to exploring projects that may appear to be completely unrelated. You might find applications for your work that you had not considered or open the door to additional research opportunities. Finally, the importance of good communication skills cannot be overestimated. A key part of your job is presenting your work at conferences and publishing it in technical journals and conference proceedings. And, you might also find that having the patience to effectively communicate and interact with researchers outside your field might just provide you with an unexpected ally someday.

Kayli Schafer

Enterprise Strategy Manager OneAmerica Franklin College BA Mathematics

During my time in undergrad, I was unsure of my next step and where my career would take me. Quite often, when I told others I was studying applied mathematics, I would get an encouraging response that my career options would be vast. At the time I was skeptical, but as I’ve progressed in my career, I’ve realized that it couldn’t be more true. I started my career in a supply chain company doing analytics and reporting. The experience was great, but I didn’t find it as fulfilling as I’d hoped. After a year, I decided to pursue a master’s degree in Public Affairs with a concentration in Nonprofit Management. During my time in graduate school, I transitioned to a graduate assistantship at a university research institute and then into the nonprofit sector. Most recently, I switched career paths yet again and took a job for a mutual insurance company in the Strategy division, but I’ve always felt that my time in the nonprofit sector was unique. Getting involved in the nonprofit sector was intentional on my part and not something I had realized possible while in undergrad. I found my passion for helping others while in Uganda my senior year but was never quite sure how my math degree would allow me to pursue this passion. Luckily, during my first semester of my master’s, my statistics professor approached me with a graduate assistantship. This assistantship gave me the opportunity to continue developing my skills in spatial, analytical and statistical software, as well as querying language and coding. With that experience, I felt fully prepared to confidently solve and analyze social issues as I began my career as a Research Analyst in the nonprofit sector. My background in math has been essential in two distinct ways. 1) It’s given me the ability to look at a problem on the surface and determine how to logically 201

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arrive at a solution, and 2) has enhanced my ability to learn querying language and other essential analytical tools to solve real-world problems using mass amounts of data. These skills have translated into any job I’ve taken on and I believe will continue to do so. During my time in the nonprofit sector, there was always constant change. The projects and issues I worked on were complex and varied, and there was never a time I found myself performing the same task. The work environment was flexible, and I had the ability to work through problems on my own and with the help of my team. The collaboration was essential in working through issues and developing the best possible analysis. The projects I was exposed to during my time in the nonprofit sector focused on fundraising analytics, as well as community and marketing research and were quite different in scope. My team helped create portfolios of potential corporate partners using predictive modeling. We determined significant factors to help engage more donors and volunteers, which took hours of data cleaning, querying and analysis. I used mapping as a tool to geographically show the significant areas of poverty in our community and how our efforts impacted those areas. Not only was I able to use my analytical and problem-solving skills, these initiatives helped our organization reach its goals and make a difference in the community, which was truly rewarding.

Jeanette Shakalli

Executive Assistant National Secretariat of Science, Technology and Innovation of Panama University of Notre Dame BS Mathematics and Chemistry Texas A&M University PhD Mathematics

I am the Executive Assistant of the National Secretary of Science, Technology and Innovation of Panama. The main objectives of the National Secretariat are to support scientific education, encourage scientific research, and to promote applications of science and technology for the benefit of the Panamanian population. (The National Secretariat is a Panamanian parallel to the US’s National Science Foundation, but on a smaller scale.) For example, the National Secretariat awards international merit-based scholarships to students for both undergraduate and graduate programs in scientific areas and finances projects on scientific research and business innovation. In my role, I analyze institutional processes and recommend solutions to all sorts of problems. I supervise coordination among the different departments of the National Secretariat and propose to the National Secretary initiatives on how to improve the efficiency of our internal procedures. I advise the National Secretary on decisions to make. I attend meetings and events as a representative of the National Secretary, revise documents before he signs them, and manage his calendar. A normal day in my job is hectic, but fun. I receive hundreds of emails per day, I revise dozens of documents, and I solve all sorts of problems. For example, the Head of Communication together with the Head of the Legal Office will come to me whenever a fake news story concerning the National Secretariat explodes on social media. As a team, we decide on the best way to approach the situation. My degree in mathematics caught the attention of the National Secretary who hired me since he valued the contributions that a mathematician could provide in a government institution. Being trained in math helps you solve all sorts of problems, 203

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and I use my mathematical background all the time in my job. Math is not about punching numbers in an equation like a robot. The study of math teaches you that the key to solving a problem is understanding it. Once you understand the problem, then you can analyze the consequences and evaluate which would be the optimal solution. Being a member of the Mathematical Association of America, the American Mathematical Society, and the Association for Women in Mathematics helps me stay connected with the math community and provides an opportunity to meet exceptional mathematicians who use a variety of methods, such as magic, mime, and music, to inspire the general public to rejoice in the beauty of math and science. Thanks to my job, I have been able to invite some of these outstanding mathematicians to be keynote speakers at scientific events organized by the National Secretariat. Furthermore, I also write articles for the National Secretariat’s magazine IMAGINA to engage the general public and, in particular, the Panamanian youth, and show them that math is fun and can be found all around us. For someone interested in a career like mine, my advice is to network. It is very important that you know the right people and that those people know you. For example, being a member of the Panamanian Association for the Advancement of Science and the American Association for the Advancement of Science has helped me to build a network in the scientific community. To be successful in a career like mine, I would suggest lots of patience and kindness. Working for a government institution, you meet all sorts of people. You never know what they have been through. Therefore, if you listen to their problems and try to find a solution together, they will be very grateful and you will feel pleased that you helped someone. Finally, I would recommend that if someone ever tells you that you are not capable of doing something, accept their words as a challenge, and prove them wrong.

Julie Shapiro

Enterprise Editor NBC News Digital Drew University BA Mathematics

When I tell my journalism colleagues that my undergraduate degree is in math, their reaction, without fail, is one of surprise – after all, they think, what could the world of numbers possibly have in common with the world of words? A lot more than you might imagine, as it turns out. The same adherence to logic and simplicity required to construct a powerful proof is also necessary to construct a fair, accurate news story. And in my job as an editor at NBC News, numbers are everywhere – from the rise of a stock price to the fall of a politician’s approval rating. I’ve worked with reporters to delve into everything from the finances of high-profile nonprofits to the struggles of America’s family-run dairy farms to the emergence of new forms of DNA testing. Math, math and more math. I hadn’t always planned to be a journalist – or a mathematician – but I fell in love with both while attending Drew University, a small liberal arts school in Madison, N.J. Math and journalism both transported me outside of myself, whether I was navigating layer upon tantalizing layer of abstraction in an analysis class or racing to file a late-night story before the student newspaper went to press. Outside of school, I spent some breaks tutoring math and attending advanced classes; I spent others interning at a publishing company and writing for my hometown paper. Journalism still felt more like a hobby than a career – and an unlikely one at that – but after graduation, I decided to move to New York City and give it a shot. I worked as a reporter for local weekly newspapers and then joined DNAinfo New York, a startup devoted to covering neighborhood news, where I grew from a reporter to an editor and discovered how much I enjoy mentoring young reporters. 205

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In 2015, I moved to TIME as a breaking news editor and later oversaw Time Labs, a data visualization and interactives team. We examined just how few actors of color are nominated for Oscars, traced the drug overdose epidemic county by county and calculated the wage gap between men and women by profession and age. Then, in 2018, I joined NBC News Digital as Enterprise Editor, overseeing investigative stories and features. My job is fast-paced and collaborative, requiring creative thinking and clear communication. As I evaluate reporters’ pitches and edit their stories, I’m constantly looking for evidence to support their claims. Often that evidence comes in the form of numbers: a narrowing margin, a shrinking subgroup, a growing trend. A math degree wasn’t required for any of the work I’ve done since college, but it may have helped me stand out in job interviews and it’s definitely helped me dive into detailed, number-heavy projects with confidence. More than anything, math taught me to think clearly, a skill that has been indispensable in my work. And I haven’t entirely left equations and formulas behind – once a week I volunteer at a Brooklyn nonprofit, where I teach math to adults who are working toward their GED. Math is, in many ways, still a part of my life, and I wouldn’t want it any other way.

Ali Shappy

Inventory Analyst The Vermont Country Store St. Michael’s College BS Mathematics Southern New Hampshire University MBA

After graduating college with my degree in mathematics, I fell into a career path in Media and Marketing. I had chosen mathematics as my major for a few different reasons. I had always loved math and had always been fairly good at it. It came naturally to me. I enjoyed how it was very black and white, right or wrong. I also chose mathematics as my field of study because I had no idea what I wanted to do after graduation, and I knew that a degree in math would be applicable in just about any job role. This was proven true as I started my career in a marketing position. There was not a lot of actual mathematics in that particular job, but I had a good base in simple problem solving and had honed my ability to approach situations with logic-based thinking and strategy. This guided me through the first few years of my career. However, I felt that something was missing. I wanted a more analytical job that challenged me mathematically. After spending two years in media, I felt stuck. I had a degree in mathematics, but only had work experience in marketing. In an attempt to round out my resume, I pursued my Master’s in Business Administration. While working full time with an advertising agency in Boston and pursuing my MBA, I was able to land a job with The Boston Beer Company (BBC) as a Regional Distribution Analyst. At last, I had broken into a more mathematical job role! In this position, I managed inventory at the wholesale level for forty-seven different wholesalers in the Atlantic region. My daily tasks included order management, forecasting based on current depletion data and past sales trends, maintaining inventory level and in-stock rating at each large wholesaler, and working collaboratively with both the wholesalers and the BBC sales reps in those regions. I was 207

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able to utilize my love for numbers and data much more freely in this role than in any other role I previously had. I enjoyed working in inventory management. I was using logic-based thinking to make decisions and was analyzing current inventory data to ensure successful business for our customers. However, I recently made the move out of Boston back to Vermont. I still work in inventory management, but now I am with The Vermont Country Store. My new job role is more complex and more interesting than the role I had at BBC. The business models of the two companies are very different. Boston Beer is the “supplier,” and I managed the inventory at the customer (wholesaler) level. Vermont Country Store is the “customer” that works with outside suppliers to bring in product, and I manage the inventory at our company level. Each forecaster on our team manages different categories. I manage Household, Kitchen, Outdoor and Food. I forecast for each product in these four categories, for each catalog, for every new season. We have five seasons we work in, Winter, Spring, Summer, Fall, and Christmas. We forecast based on revenue we expect the product to bring using criteria such as historical revenue and web and catalog visibility. Once everything is forecasted for each catalog of that season, we turn to inventory management, considering both minimum order quantities (smallest quantity of an item that can be ordered from a vendor) and what we currently have on hand for each product. As a catalog gets in-home and we start seeing sales come in on certain products, we can double check and see how our forecast is doing compared to what the system is projecting based on the current rate of sale. We work with planners to get new purchase orders in place or cancel outstanding purchase orders if demand does not align with forecasting. Forecasting is our main job role, but there are plenty of other tasks that we have to do on a daily basis. We communicate with our creative team to cross check upcoming catalogs with what we have in the system. We build out reports to ensure that inventory is prepared for email or website promotions. I also work on liquidating discontinued product, determining what pricing is best to get the product out the door, and deciding when a product should be put in bargain bins or donated. There are a lot of different facets to this job, which keeps it exciting and fast paced. Every day is different and every day you learn something new. It’s a collaborative role with many different areas of the business, which allows for a broader perspective on how things work and how other departments are affected by decisions. My mathematics degree has given me all the tools to be successful in this role. I often spend my days looking at numbers and deciding which number most accurately represents the potential of each item. I also am able to organize my daily tasks in a logical and prioritized manner, as there are constant changes and ad-hoc tasks that we need to complete. Mathematics provides a necessary base knowledge, not only in numbers, but in the general thought process and decision-making. I am confident that I can successfully take on any new responsibility or job role with a base knowledge rooted in mathematics.

Richard Sharp

Data Scientist Starbucks Northwestern University BS Mathematics and Integrated Science Princeton University PhD Applied and Computational Mathematics

I am a data scientist with the business strategy team at Starbucks. My journey to the data science field, along with many of my colleagues, followed a roundabout path. I originally studied numerical analysis and scientific computing, rather than taking the machine learning/artificial intelligence path in computer science. In school, I studied modeling with multiscale numerical methods with applications to quantum chemistry and materials science. My first industry job was with Microsoft, where I worked on Azure ML, a cloud-based machine learning platform. It was a great place to learn some fundamentals of software engineering, and there were new numerical challenges as well: how do you run calculations in the face of ever-changing, ever-growing data? From there, I moved to the data science team at Amplero, a startup that specializes in personalized marketing, and finally to Starbucks. My recent work has focused on personalization, using data from multiple sources to determine the most relevant way to treat an individual. Typically, the treatment comes in the form of an advertisement, though it can mean any interaction that improves a customer’s experience. Personalization through data has made inroads in a number of areas, such as medicine (for example, Penn State Statistician Susan Murphy’s exciting work with just-in-time adaptive interventions). By making intelligent choices about the content and strategy for sending messages, including whether to send one at all, recipients are more likely to receive relevant, timely information. I rely on my mathematics background, especially optimization, control theory, random variables, and experience with powerful representations of data like wavelets. My daily work is a combination of the theoretical (mathematical analysis 209

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of current processes and proposing new designs) and the practical (building proofof-concept implementations to demonstrate the theory and building the business case for implementation). My ad hoc run-ins with software engineering help as well, in particular learning to think not just of how to build a particular model, but how to integrate it as a core component of a continually running service. It’s necessary for a model to produce good results on a test set (a historical snapshot of data), but how will the model actually behave in the continual stream of data in the production environment? The biggest change, mathematically speaking, in moving from traditional numerical analysis to data science has been transitioning from problems that are defined by computational complexity to ones where the computing challenge lies in the volume and velocity of the data. Likewise, the modeling challenge has shifted from the deterministic (laws of physics) to the stochastic: a fascinating and humbling attempt to understand human decision making. Nevertheless, computationally intensive simulation, one of my old standbys, has its place. Monte Carlo style simulations, typically in support of Bayesian models, are common. These can be used for verification; that is, testing that a new personalization strategy works in the idealized case where you can prescribe the response of the simulated individuals. Data science can be a good fit for anyone with a mathematical background. My colleagues come from a variety of backgrounds (mathematics, statistics, computer science, physics, and biology). There are some fundamentals that you may have more or less experience with depending on your background. These include an understanding of statistics and the ability to write software. There is no single, correct language to learn, but a typical example and current favorite is Python. Writing code is an essential skill because it makes you independent. Real data is messy and comes in many formats. Being able to obtain, shape, and model that data on your own quickly gets you to the point where you can discuss the model’s worth rather than be mired in obstacles preventing its construction. There are many websites, courses, boot-camps, and meetup groups out there that help you build up the skills you need. Curiosity and an ability to think about the difference between the mathematical and real-world behavior of the model are essential. I find myself in coffee shops a lot these days, trying to understand what the numbers on the screen mean in real life. To read more about my work, check out: http://www.geekwire.com/2016/ starbucks-using-artificial-intelligence-connect-customers-boost-sales/

Danielle Shepherd

Simulation Engineer Chip Ganassi Racing College of Wooster BA Mathematics and Physics

Hindsight is always 20/20, but sometimes, while you are on the journey, you don’t realize the importance of the steps you are taking. When I started school at the College of Wooster, I never thought I would end up in the auto racing industry. After my first semester, my love for math and physics emerged, and I decided to pursue racing. Growing up, I had always been a fan of the sport, attending my first race at the age of 6. So, I had decided to pursue racing as a career, but the question now was how to obtain that goal. After declaring my mathematics major, I was assigned a professor as an advisor. One day during my junior year, he called me into his office. By chance, he had just been to a conference where he heard a presentation by a professor at Davidson College involving mathematics related to NASCAR. I applied to work with this professor, was accepted, and spent my summer interning at Davidson College, collaborating with a NASCAR team. While in Charlotte, I was put into contact with a College of Wooster alumnus, who would ultimately help get me my first job in racing. He talked to me about the different aspects of the industry, told me to remain persistent, and advised me on the best way to pursue my career. After I graduated, with my internship experience and information from the alumnus, I started sending emails to race teams hoping for a position. At first, I hardly got any responses and, when I did, it was to say that nothing was available. I got a job working as a development technician for a company that made liquid crystal writing tablets. This was a great first position for me. I enjoyed the work; however, deep down, I really wanted to pursue racing. I continued to email with teams, still not 211

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receiving positive feedback. I started calling race engineers, to make more contacts and get advice on how to strengthen my resume and become a good candidate for an engineering position. Then, the call I had been waiting for came. I was offered a position as a DAG, the basic engineering role, on a race team. Two weeks later, I had moved to Indianapolis and was travelling to races with the team. There is a tremendous amount of data that is generated each time an IndyCar runs. It is imperative that the data system on the car work correctly and produce accurate information for the engineers to make beneficial changes to the car. A DAG’s job is to make sure this data collection process works, to make sure the sensors on the car provide accurate information, and to help analyze data. Math, physics, and the whole process of being a scientist are important for this position. Learning how to efficiently and effectively analyze data, find problems, and correct those problems in a timely manner are important aspects of this job. I spent two years working as a DAG at KV Racing, and then I moved to Chip Ganassi Racing as an assistant engineer. The assistant engineer role is similar to the DAG role except there is more of an emphasis on analyzing data and assisting the race engineer with the changes made to the car. After one year as an assistant engineer, I moved into a role as a simulation engineer. The goal of this position is to run different car setups through a simulation to determine the effects on lap time and handling. Math, physics, and programming are a part of the development of the simulations, as well as the analysis of the results. When it comes to careers in mathematics or really the decision on any career, I think it is important to remember to never give up. You don’t have to know exactly where you want to go, just remember to be true to yourself and work hard. The path may change along the way, but at each step make sure you are working toward something. In the end, once you reach your goals, you can turn around and see the path that led you there. It may not be what you thought, but always be persistent.

Benjamin P. Simmons

Vice President, Risk Solutions Gravie St. Olaf College BA Mathematics

I have always had broad interests, both academic and beyond. There was little doubt in my mind that I would study and major in math, which was always my foremost academic interest, but I had questions about what else I would study alongside math and what I would do with a math major after school. After engaging in research in pure math, applied math, and mechanical engineering during college, I realized that I preferred to use my math background more broadly (albeit perhaps less intensively) in service of a career in business. I was passionate about renewable energy and joined an energy management and consulting firm after college. I began as an Associate, doing analysis for the strategic planning division that was focused on projecting clients’ future energy needs and assessing the economics of building new power plants. My statistics background was useful for this. Soon after starting, I also joined the team charged with building a bio-energy power plant that generated electricity from recycled agricultural biomass. The plant would anaerobically digest biomass, like corn silage or manure, to produce methane gas that was then burned to generate electricity. I procured some of the equipment for the facility and then managed vendors and contractors as it was being built. Not long after the plant was constructed, I moved into the role of Asset Manager, where I was responsible for the business operations of the power plant. The transition to that job was like learning to drink from a firehose! But my math background helped: the same approach one takes to learn a foreign mathematical concept – dissect it, observe structures, recognize patterns, and arm oneself with tools to solve problems in that field – applied also in this context to learning new things that were foreign or overwhelming (like the 213

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electronics of a power plant or the biology of anaerobic digestion), understanding them, and applying them. When the opportunity to join a healthcare tech startup, Gravie, emerged, I made a change. There, my initial work focused on the business operations of a very different sort of company. I have had several roles at Gravie (not uncommon at a startup), and most recently—and most rewardingly—I led the initiative to start Gravie’s own insurance company and develop its own health insurance products. I now manage these product lines and the insurance company that backs them. There is a good deal of math that underlies insurance, and I have found that my studies of probability theory and Monte Carlo simulations have been especially useful. For instance, some of my responsibilities have included selecting actuarial firms; contracting with them to develop pricing models for our insurance products; overseeing that development; and managing our assessment of risk. Having some background in the relevant math has been invaluable. More broadly, when one works at a startup, one has to be comfortable living with a tremendous amount of uncertainty. When the startup involves insurance, that adds an extra layer of uncertainty to the mix. I have found that a background in math has equipped me well to live in a world of uncertainty; I learned in college math courses how to approach (and ultimately solve) ostensibly impregnable problems with an open mind and with the confidence that a solution did exist. The same approach works well at a startup. It’s important to ask lots of questions along the way and also to be able to make good decisions with limited time and information, with which creative problem-solving skills (broadly) and mathematical estimations (specifically) both help. If faced with the opportunity to start over, I would surely major in math again; it has provided both a strong and flexible foundation to successfully and deeply pursue a variety of interests, as desired. (QED.)

Andrew Stein

Associate Director of Pharmacometrics Novartis Massachusetts Institute of Technology BS Mechanical Engineering MS Mechanical Engineering University of Michigan PhD Applied Mathematics

I work as a pharmacometrician, developing mathematical models of biological systems based on in vitro, animal, and human data in order to enhance our understanding of diseases and to support decision-making in the pharmaceutical industry. In a typical week, I’ll spend time reading papers, exploring data, developing models, writing reports and publications, and most importantly, collaborating with drug development teams to understand the most important problems they are facing, and then brainstorming ways in which my group might help. I also regularly attend conferences and seek out collaborations with academic partners. Pharmacometrics requires expertise in a range of areas including mathematics, statistics, biology, and pharmacology. It is unlikely for someone to have a strong background in all these areas, and so continuing to learn on the job and to collaborate with others is important. My mathematical education has been particularly useful in that it has given me a deep understanding of differential equation models and optimization algorithms. On a typical project, I might use differential equations to model the link between the dose of a new drug, its effect on safety, and its efficacy. These models are then used to help design trials and to identify the optimal dosing regimen for patients. When a model doesn’t fit the data well or an optimization algorithm fails to converge, a deep mathematical understanding helps me to more quickly understand and solve these issues. As a student, I always loved mathematics and biology, though it took me a while to figure out how best to translate this into a career. I started out studying Mechanical Engineering with a focus on Biomedical Engineering because I thought I might choose a career developing medical devices. I found what I enjoyed most was 215

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learning how the same mathematical equations could be used to describe mechanical, electrical, and biological systems. I later decided to pursue a PhD in Applied Mathematics to learn more about the mathematical tools used for describing these systems. While in graduate school, I did a summer internship at Novartis. This was a rewarding experience, and it led to me joining the company four years later. For a career in pharmacometrics, a PhD or PharmD is generally required since developing a new drug is a research enterprise, and earning a PhD is the standard path toward learning to do original research. Summer internships can also help you to determine if this is a career you’re interested in, and they can help you to gain valuable experience and to make connections. Overall, I have found this to be a rewarding career. Every day, I get to think about new problems in a variety of different fields: mathematics, statistics, biology, and pharmacology. I interact with a number of smart colleagues and learn from both my senior colleagues who continue to mentor me and my junior colleagues who teach me a lot as I mentor them. Overall, the work-life balance allows me plenty of extra time to take singing lessons, play the ukulele, and travel.

Jean Steiner

Senior Director of Data and Insights Skillshare Princeton University BA Mathematics University of California, San Diego PhD Mathematics

According to the Harvard Business Review [1], data science is “The sexiest job of the 21st century.” While it’s hard to argue with a “sexy” job, you may be wondering just what the job entails! As a data scientist, I apply the scientific method in order to answer questions with data. Currently, I work at an online learning platform called Skillshare, where I use data and insights to connect the lifelong learners who use our product with great courses. Previously, I was at an oncology data analytics company called Flatiron Health, where I used data to provide insight into oncology patient outcomes with the ultimate goal of improving cancer care. Prior to Flatiron, I worked at Google, where I used data to improve experiences for users of Google search as well as for our advertisers. To give a feel for what data science might be like, I will describe the process of a project I worked on at Google. Our goal was to quantify the long-term effects of ads on user behavior. If you are curious to learn more about the project and our findings, it is described in depth in a longer article [2]. The project was inspired by the theory that if a user saw a low (or high) quality ad and had a bad (or good) experience today, this might affect the user’s behavior towards ads in the future. We would say that a user might develop “ads blindness” (or “ads sightedness”). As a data scientist, I help translate this intuitive idea into something quantifiable and then test out the idea with data. After we had our basic hypothesis, “ads affect long-term user behavior,” the first step was to define metrics that would capture the user behaviors we care about and translate the intuitive idea into metrics we can quantify (we primarily used click-through-rates, which describe how frequently users click on ads). Next, we designed a study to detect movement in the metrics of interest (in this case we had a complex study design that was a combination of so-called “A/B” and “A/A” 217

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experiments, and it is described in detail in the article cited above as well in this Google blog-post [3]). After we developed and refined the study design and had the support of business leaders, we carried out the experiments (here I worked closely with software engineers to ensure the experiments worked as intended). Then we collected and cleaned the data and computed the metrics (this was the most timeconsuming part of the project – cleaning and gathering data accounts for as much as 60-80% of a typical project). Once we had our data and metrics, we used statistical methods to determine whether our hypothesis held (it did in this case!). We also had some unexpected findings that we needed to explore in subsequent experiments. Finally, we shared the results with key business leaders to ensure our findings led to appropriate business decisions. I enjoy working as a data scientist because I like the mix of activities: from working with colleagues to frame a problem and translate an idea into a testable hypothesis, to getting the right data, analyzing it, and finally sharing results. I also enjoy the fact that there are many opportunities to keep learning as a data scientist: ranging from learning a new statistical method to learning a new domain (such as oncology). My favorite part of any project is finding the story in the data and then using those findings to support better decision-making. I ended up in data science after starting my career as a mathematician. My advanced mathematical training has been a great foundation because I developed valuable transferable skills including rigorous problem solving, the ability to understand complicated systems, and the ability to learn new quantitative methods. Core math classes (calculus, linear algebra, differential equations) provided a great foundation, as well as giving me the ability to learn additional analytical methods. The other key technical tools that I use on a daily basis are statistics, basic programming, and databases. If you are interested in becoming a data scientist, I strongly encourage you to augment math courses with basic statistics, programming, and hands-on work with data through projects (in addition to coursework that includes projects, you can explore internships, several summer programs focusing on “data science for social good” at the University of Chicago and University of Washington, on-going volunteer opportunities with organizations like Data Kind, and online data science competitions hosted by Kaggle and others). Data science can be a great field if you enjoy mathematics and quantitative reasoning – it is a fun way to solve problems with data, and there are a lot of job opportunities. As more businesses and activities shift online, there will be more data to analyze and an increasing need for more people to work as data scientists and analyze that data. [1] Thomas H. Davenport, D.J. Patil, “Data Scientist: The Sexiest Job of the 21st Century,” Harvard Business Review, October 2012. [2] Henning Hohnhold, Deirdre O’Brien, Diane Tang, “Focus on the Long-Term: It’s better for Users and Business,” Proceedings 21st Conference on Knowledge Discovery and Data Mining, ACM, Sydney, Australia, 2015. [3] Henning Hohnhold, Deirdre O’Brien, Diane Tang, “Experiment design and modeling for long-term studies in ads,” Unofficial Google Data Science Blog, October 7, 2015.

Courtney Stephens

CEO QED Energy Associates Centenary College of Louisiana BS Mathematics

After college, I wasn’t quite sure what to do with my mathematics degree. I had chosen mathematics as a major because I love problem solving and always found the subject challenging. Without a clue of how mathematics can be applied in the energy industry, I sent my resume off to a few recruiters in Houston and got several immediate responses. It turns out that math degrees are sought out in the energy industry for the role of Reservoir Engineering Technician. It’s a fancy title for “modeler and data analyst,” which my professors would have referred to as “Operations Research.” I started my career as a Reservoir Engineering Technician at an engineering consultancy. I worked as part of a multidisciplinary team that modeled future oil and gas reserves, production, and profit. The team included geologists, geophysicists, reservoir engineers, and reservoir engineering technicians. It was my job to analyze the historical cost, price, and production data to determine input parameters for the models. I was also responsible for running the model, performing sensitivity analysis in conjunction with the reservoir engineer, and checking the model for errors and accuracy. I then moved to an investment bank specializing in oil and gas transactions. Investment banks are sort of like the realtors of the oil and gas industry, helping companies to buy and sell oil and gas properties. In addition to modeling reserves and economics, it was my responsibility to locate synergies within the industry. For example, if Company ABC has one thousand gas wells in Texas and one oil well in 219

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California and Company XYZ has one thousand oil wells in California and one gas well in Texas, doesn’t it makes sense to coordinate a trade? Worldwide, there are thousands of databases that one can mine and manipulate to find potential value. When I was ready to slow down, I moved to an oil and gas company. Oil and gas companies are known for having great work/life balance. While at this company, I worked on the budget planning team, the exploration team, the production and operations team, and the business development team. It was exciting and thrilling to see how large teams of scientists work together to safely and carefully produce the energy America needs. After having my son, I reflected for many months on the great opportunities the oil and gas industry had afforded me. Over the years my phone rang time and time again with recruiters throwing out larger and more outrageous salaries. I had the thought, “Could I make copies of myself?” Could I engage new mathematicians to come and learn under my guidance and set them up for a career in oil and gas? It took a lot of soul-searching, but in April 2010 I started my own firm for just this purpose, QED Energy Associates. At QED Energy Associates, my team makes best-in-class Reservoir Engineering Technicians and places them at top-notch industry jobs. Recent math-minded graduates train with us for six weeks to learn the ins and outs of the oil and gas industry, then we are paid by our clients to gain access to our super candidates. I was named Young Entrepreneur of the Year in 2012 by the Houston West Chamber of Commerce. I am proud to have made it through the commodity price downturn of 2014-15 without having to lay off a single employee. I have helped over two hundred recent grads get started in the oil and gas industry. If you are interested in following a corporate path, please reach out to us for more information. We would love to have the opportunity to speak with you.

Sumanth Swaminathan

Chief Data Scientist Revon Systems Inc University of Delaware BSE Chemical Engineering Northwestern University PhD Applied Mathematics

I got interested in data science in 2014 when I was working at W.L. Gore & Associates as an internal quantitative consultant. After doing some preliminary studies on the subject, I applied for and got accepted into the Data Incubator, which is a New York City-based fellowship that trains quantitative talent in cutting edge data science methods and places them in top industrial positions. The health technology startup Revon Systems Inc recruited me out of this program. Now I’m the chief data scientist at Revon Systems Inc. My primary job is to build and direct the development of machine learning models that are used to detect disease flare-ups in patients with chronic illnesses and provide a recommendation on the appropriate responsive action. As a member of a small startup, my day-to-day activities are wildly varied. On any given day, I could be writing algorithms, building statistical designs, running application testing, studying clinical research papers, interviewing doctors, supporting fundraising efforts, giving academic talks, or recruiting and mentoring new talent. These are all in addition to the normal meetings and administrative duties that come with any industrial job. I work from home, but I travel about 30% of the time for client visits, collaborations, and office visits. Any given work day at home is also 25% conference calls and video meetings. Having a rich understanding of mathematics is the single most important thing in my career. It has armed me with necessary hard skills in algorithms and general 221

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quantitative methods, but it has also armed me with the essential critical thinking skills for generating value in companies. Both my former position at W.L. Gore and my current position at Revon Systems Inc were realized because of my interdisciplinary background in academics and work experiences. My PhD in mathematics was essential for the primary job functions (quantitative consulting and machine learning), but my background and contacts in engineering are what made me stand out as a candidate for W.L. Gore. Similarly, my leadership experience at Gore and my successes in scientific publication, talks, and product development made me a standout candidate at Revon. Revon’s major product is a mobile application that utilizes machine-learning predictions to identify exacerbations in chronic obstructive pulmonary disease patients and provide associated guidance on the appropriate medical attention to seek. Patients who use the app enter health data into the phone on a regular basis. When they are concerned about their symptoms, they can activate the “Am I Ok” process and get on-demand decision support about their current health. Training of the algorithms required a full sweep of empirical model building activities including training and validation data acquisition, data cleaning, descriptive data analysis, machine-learning algorithm training and validation, parameter studies, and algorithm deployment. Most of this work requires good knowledge of scripting languages and statistical packages like Python and R. Work and family balance always depends on the institution in which we work and the culture that is practiced by our coworkers. In my particular company (as is true in many startups), I am often required to be on-demand for a variety of work activities. However, work-life balance is important to my company, and I rarely find myself in a position where I have to compromise my personal life because of company demands. In general, work-life balance is a very important issue to consider when choosing a career. There is no question that doing quality hard work in graduate school with recognizable success metrics (talks, publications, grades, etc.) was crucial to me finding a good career. However, it was almost equally important to engage in outside project opportunities (internships, consulting opportunities, competitions, etc.), network with professionals, and develop good professional skills (writing, communicating, meeting deadlines, documenting work, etc.). Finding a good career requires making a case for one’s own value, and all of the items that I mentioned are integral parts of a great case.

Rebecca Swanson

Teaching Professor Colorado School of Mines Dakota Wesleyan University BA Mathematics Indiana University MA Mathematics PhD Mathematics

There are many types of academic jobs, but all usually consist of a mix of teaching, research, and service to the department, university, and mathematical community. As an undergraduate mathematics major, I was drawn more to the teaching and service aspects of academia, and I was excited to (later) find out that there are jobs out there whose primary roles are teaching and service. As a Teaching Professor, I teach a variety of mathematics courses at multiple levels. I enjoy the challenge of helping students learn mathematics, and I especially like the way that my schedule changes from semester to semester. Even when I teach the same course, I can always experiment and change how it is done. Additionally, my “teaching” extends outside of the classroom into my service roles: I advise students on classes and careers, I co-advise our Putnam (mathematics competition) team, and I co-founded our local Association for Women in Mathematics Chapter. Research is not required in my position, but it is valued. When I’m not spending time teaching or participating in service, I spend my “research time” studying best practices for educational development. I enjoy working to improve what I do in the classroom, and I’m constantly learning about, implementing, and measuring the effectiveness of novel teaching practices. Although I now have a job that I enjoy, I did not always know what to do with my interest in mathematics. In high school, I spent most of study hall helping other students with their mathematics homework. A friend of mine noticed this 223

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and suggested I attend a summer program called Governor’s School. I had such a wonderful time learning more advanced mathematics that I decided to major in mathematics in college. However, I had no particular career goals in mind when I was a first-year college student. My college advisor told me about the Summer Math Program for Women at Carleton College, so I applied and attended the following summer. The program taught me even more interesting mathematics, but in particular, it opened my eyes to the possibility of attending graduate school, as well as other summer and semester mathematics programs. Even though I was unsure of what to do with my upcoming mathematics degree, I knew that I enjoyed the subject and spent some of my subsequent summers and semesters doing mathematics research in a Research Experience for Undergraduates, studying abroad (Budapest Semesters in Mathematics), and studying elsewhere in the US (Mathematics Advanced Study Semesters at Penn State). In the midst of all of this, I returned to my home institution and still didn’t have a career plan. I considered teaching high school, but enjoyed collegiate-level mathematics. I job shadowed an actuary, but didn’t feel like that was for me. My advisor Dr. C seemed to have so much fun at his job and always had variety in his schedule since he was teaching different classes every semester. Reflecting upon what I saw in Dr. C’s job and my own interests, I decided to attend graduate school with the goal of being a college professor in a more teaching-oriented role. During graduate school I was exposed to academic positions whose primary focus was research and whose secondary emphases were teaching and service. During this time, I had doubts about my future. I often enjoyed research but was not passionate about it. Because of this, I often felt like a failure. It took some time to realize that I had the power to define my own success. After completing graduate school, I spent a couple of years at a small liberal arts college before moving to my current position, which values quality teaching and service, but also supports any research I wish to pursue. Those interested in attaining a position like mine will typically need to obtain a doctorate in mathematics or mathematics education. You will need to ensure that your graduate program provides you with sufficient teaching opportunities and perhaps the ability to stand out amongst your peers in this regard. If you are not sure that this is the career path for you, try out a variety of experiences such as undergraduate mathematics research, internships, job shadowing, or other mathematics programs that are available. While pursuing these opportunities, be mindful of aspects that you like or dislike. For instance, I enjoyed my undergraduate research program, but I realized that what I primarily enjoyed was working with the other students—the math was somewhat secondary. Or, when I job shadowed an actuary, it seemed as if the job didn’t allow for enough day-to-day variety for my taste. Identifying the aspects of these experiences that you enjoy will make building a career that you love that much easier.

Shree Taylor

President & CEO Delta Decisions of DC, LLC Clark Atlanta University BS Mathematics MS Mathematics North Carolina State University PhD Applied Mathematics

I am the President & CEO of Delta Decisions of DC, LLC (Delta Decisions), a management consulting firm that specializes in analytics. We collect, analyze and translate data into meaningful information and valuable insights that support confident leadership, planning and decision-making. I founded Delta Decisions with two classmates from North Carolina State University: Dr. Kim Woodson Barnette and Dr. Afi Davis Harrington, both of whom majored in Operations Research. Prior to that, we were all analysts at CNA (formerly the Center for Naval Analysis). There are no normal days and that’s what I love about what I do! I spend my time using my technical expertise to help solve a client’s problem, meeting with employees to ensure that expectations are being met, writing proposals to get new work, interfacing with all of my business vendors to make sure that the company’s operations are continuous, networking to find new partners and clients, interviewing top talent and anything else that needs to get done! And that’s just my day at work. Before and after work, I am focused on making sure my family is taken care of and has lots of love. Every day is like a new optimization problem that has new priorities (objective function), assumptions, and constraints. My work environment is both solitary and collaborative, but mostly collaborative. I prefer to brainstorm initially in a solitary environment with a white board. After developing a methodology or approach to a client’s problem, the work becomes highly collaborative as the team’s various skill sets come into play for implementation. Having degrees in mathematics has trained me how to logically dissect and analyze problems. In consulting, clients have problems that they either don’t have the time to think through or the expertise to solve. In some cases, they are not 225

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even sure how to articulate their problem. Observing and active listening are critical skills in consulting. I approach all of my client’s problems as if they were a math problem! I take time and care in making sure that the problem is well defined and that I understand the various constraints that the client may have (e.g., political, budgetary/financial, cultural, etc.). I use this information to determine an approach to address the problem. I review the approach with the client and make adjustments as needed based on their additional feedback. This phase occurs many times over the course of the project as I must remain aware of any changes in the problem we are trying to solve and the conditions. An example of how I use mathematics on a project I support is in the area of workforce planning. A client has several worldwide locations and wants to know how to best staff their locations. Each location is different and there is data associated with all locations. After collecting and analyzing several years of data, machine learning is used to determine the appropriate ranges of staff at each location based on various parameters. Balancing work and family is tough, but doable. My family is my priority and every day is different. In my household, every Sunday evening, my husband and I review our schedules and we determine our priorities for the week. There are times when he may have an early morning meeting or needs to travel internationally. I will schedule meetings around my daughters’ school and after-school activities. If I have early morning meetings or need to travel, my husband will plan his work schedule around the family’s priorities. Since schedules are dynamic and change frequently, it’s important to be flexible and to utilize technology (e.g., web-based meeting platforms) when necessary. Someone who wants my job should be a courageous, creative, and out-of-thebox person. They cannot be risk-averse, as there is a lot of risk associated with being an entrepreneur. There is no one route to follow for my career, or any career. However, whatever you want to do in life, you must be passionate, committed, and decisive. In turn, you will be happy, and you will have a positive and influential impact on society. Be brave enough to do what you want to do; be brave enough to create your own happiness.

Alec Torigian

Associate Director, ACE Teaching Fellows Alliance for Catholic Education University of Notre Dame Saint John’s University BA Mathematics and Peace Studies University of Notre Dame Master of Education

As an associate director of ACE (Alliance for Catholic Education) Teaching Fellows, I get to play a role in leading a team that recruits, selects, trains, and supports college graduates from all backgrounds as they live in an intentional community and teach in under-resourced Catholic schools across America while earning a cost-free Master of Education degree from the University of Notre Dame. I teach a course on middle school classroom management, lead workshops in cultural competency, accompany individual teachers and communities of teachers through the ups and downs of the first years of teaching, plan and lead retreats, and supervise a team of ACE graduates as they work to support our teachers. I have the privilege of meeting with principals and superintendents across the country to ensure that we are serving their schools as best we can, and I recently have had the joy of helping launch a new initiative aimed at closing the opportunity gap and recruiting more college students from the communities we serve to consider teaching via a dynamic summer experience for middle school students in which they are taught by college students in teaching internships. After obtaining my degree in mathematics, I spent a year teaching math and physics in a village in Tanzania. After that, I became an ACE Teaching Fellow as a middle school math and science teacher in Mobile, AL. This teaching experience led to an opportunity to join the ACE staff, and three years on staff (and two additional years of teaching in Chicago, IL) led to my current leadership role in the organization. While I’m based on campus at Notre Dame, I spend a good bit of time traveling, whether it’s to recruit future teachers at college campuses across the country, to 227

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check in on our teachers and school partnerships, or to help run our new initiative that we’ve piloted in Arizona. While I often miss teaching, I’m very grateful that my current role has me constantly working collaboratively with new teachers, seasoned school leaders, and our team of educators here at ACE. It’s no secret that there is a great need for strong teachers in the STEM fields, and I remain grateful that I was able to get my foot in the door with a teaching program like ACE that afforded me the chance to use my content knowledge and build teaching acumen. I heard so many people say that studying mathematics would help with broader problem-solving, and I have to admit that they were correct. Whether it’s thinking through the puzzle of which applicants might fit best in which schools or more directly crunching the numbers of how we can be more economical about the rent we subsidize in community housing, I put my degree to work daily in various ways. Teaching in an under-resourced school was more of a lifestyle than a job, as the work will always expand to fit the time you allow it. I have carried a similar intensity with me into my current role, but enjoy much more flexibility. I have had the chance to take trips home and visit friends for work and in between work, and I have learned a lot about creating my own timelines and schedules. It’s been really great having a more flexible schedule. Looking back, I benefitted greatly from the variety of mathematics courses that built on more than just number sense but pushed me to think abstractly, problem-solve, persevere when seemingly small challenges required a great deal of time and attention, and critically analyze reasoning. Additionally, much of the confidence and success I experience in my current role has been guided by my experiences taking on leadership and experiencing failure and discomfort. Whether it was a math class or a volunteering opportunity, the experiences that have made me more comfortable with discomfort have made me a better employee, leader, coach, mentor, friend, teacher, and a better human in general. I certainly remember enjoying some mathematics courses more than others, but I almost always worked in study groups, and I’m grateful to every one of them for those lessons in perseverance and the belief that we can do hard things together. I have been very fortunate to leverage my math degree in a way that has allowed me to spend my first decade out of college playing a variety of roles in a small handful of different jobs, but I am most grateful for the fact that I’ve been able to use it to directly and indirectly serve children and communities who have been marginalized and who deserve all the love, care, and quality education that we would want for our own children.

Robert Troy

Pilot US Air Force Saint Michael’s College BS Mathematics

I am a Lieutenant Colonel and an F-16 pilot in the Minnesota Air National Guard. I always wanted to fly airplanes and flying military airplanes, because of their speed and maneuverability, particularly interested me, as I’m an adrenaline junkie. Being in the Air Force was one of the reasons I picked the college that I did. My plan was to join the ROTC program and try for a pilot slot. That didn’t work out. The college phased out the ROTC program the year I arrived. By more of a coincidence than anything else, my junior year of college, a pilot from my hometown wrote a book about his military flying experience. I read it, called him up and asked for his advice on how to get into the Air Force. New motivation was born. I graduated from college, and following the recommendation, applied for Officer Training School. I was selected for a pilot slot, and that’s how I got into the Air Force. I fly between six and twelve times in a month. So obviously, not every day involves getting into the air. The days I don’t fly used to be spent reading tactics, talking with other experienced pilots, and preparing for the next flight. Now, after eighteen years in the Air Force, with higher rank and experience, they’re spent doing any of a hundred other tasks that are required to keep a squadron running. I manage people, go to meetings, coordinate training, write performance reports, etc. Fly days start with mission planning, either the morning of the flight, or the day before. Next we brief. This usually occurs between one and one-half to two and one-half hours prior to takeoff. The brief covers every aspect of the flight in pretty significant detail. It can be very specific or very general based on the complexity of the mission type. After the brief, we step to the jet, preflight, strap in, start, taxi 229

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to the runway, then take-off. This takes between forty-five minutes and an hour. Our flights can last as short as forty minutes, and my longest is almost eleven hours (Hawaii to South Korea). After the flight, we debrief. This is where most of the learning happens and can last for several hours. My work environment, outside of flying, is very similar to an office environment. I have an office with a computer where I do most of my work. There’s a vault (to protect the sensitive nature of the information) that contains all of our tactical literature as well as computers for mission planning. The squadron I’m in could have anywhere from twenty to fifty people working in it on any given day. It’s a very collaborative environment. However, when I fly, I’m the only person in the airplane. I talk with my crew chief on headset when I’m starting the airplane, and have communications with my flight-mates for the rest of the flight. We typically fly with two or four airplanes, depending on mission type. My math degree didn’t help me find my career. I pursued this career because I’ve always wanted to fly. The fact that this career uses math as much as it does, and I have a degree in math, is a lucky coincidence. Math has given me a good foundation in problem solving. It has helped me develop grit for solving different tactical problems and taught me to look at things from different perspectives. Being very analytical is important, in my opinion. Math is used in flying the F-16 in several different ways. There are performance calculations: determining the appropriate distance to start descending to minimize fuel expenditure, or figuring out the correct approach speed based on a fuel state, or how much time I can support a person on the ground before I have to leave and get fuel based on my fuel flow. There are also tactical calculations: calculating the ranges we can shoot a missile at the “bad guy” and still turn around and defeat any missiles that were shot at us, or determining how many bombs we need to drop to achieve the desired weapons effect. Computers do 99% of the work for us, but there is always the simple formula that gets scribbled down or talked about around the mission planning table. All the preparations on the ground help to make the math in the airplane a little easier and more accurate. Balancing work and family is always a challenge. As a pilot in the Air Force, you can expect to deploy. Whether it’s to a training opportunity for a week or two, or a combat deployment to a garden spot in this world, it will probably happen. Every family deals with this differently, and some better than others. Communication is the key. The advice I would give someone who wants my job is nothing more than if you want something, work hard to achieve it or exhaust every option until it’s clear you cannot obtain it. Much like a difficult math problem. In my job, I’ve seen people from every educational background. I think a math background has given me a great head start, but the most important thing is a willingness to learn and a good work ethic. Nothing cosmic. I see people that are very technologically inclined do well in this profession, but as long as you’re willing to learn and have the capability to learn, you’ll do just fine.

Jane Turnbull

Assistant Vice President Equifax The University of the South BS Mathematics Northern Illinois University MS Applied Probability and Statistics

My current role is Assistant Vice President in the Predictive Sciences department at Equifax, the credit reporting agency. It is a fast-paced role that requires many different skill sets including analytical, programming, organizational, multitasking, managerial, and business. The wide variety of tasks that I perform every day and the speed at which I must accomplish these tasks are what keeps me energized and engaged. While I was in graduate school, the medical and pharmaceutical research career path was emphasized. I was absolutely excited about this type of job opportunity because I could use my favorite analytical tool, design of experiments, in a real world environment. Upon graduation, I relocated to an area of the country where very little research of this type was performed, and due to the recession, it was quite difficult to find a job. I took a position as a statistical modeler at JCPenney Life Insurance Company (now Aegon Direct Marketing Services) and built insurance response models for their direct marketing and telemarketing campaigns. I discovered that even though I was not using design of experiments, I loved what I did for a living. I realized that as long as I could play with data, regardless of its source, apply mathematical and statistical concepts, and formulate valid conclusions, I would be professionally satisfied in any type of analytical role. Since my time at JCPenney, I have worked for several other financial services and database companies, including Acxiom, Conseco Finance, and now Equifax. For each of these companies, I built many different types of predictive models using 231

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various types of multivariate regressions for marketing and risk applications in credit card, wireless, mortgage and insurance industries, both domestic and international. With each company, I continued to grow professionally, and I have been promoted to positions of greater responsibility. Currently, I manage a large analytical and statistical team that is responsible for delivering predictive models for Equifax customers. While my analytical capabilities are central to my success, I believe that the respect I have for each member of the team as well as my ability to successfully meet business timelines are equally important. While I do not delve as deeply into the data now as I did before, and I do sometimes miss the feeling that I am actually producing something of value, I am passing my business and analytical experience on to junior statisticians and analysts, and I am gaining additional experience in the strategic role that analytics and predictive modeling play in the strategic value propositions of Equifax.

Jasmin Uribe

Research and Development Computer Scientist Sandia National Laboratories University of Arizona BS Mathematics MS Applied Mathematics MS Computer Science

Mathematics has always played a significant role in my life; my father was a mathematician, my mother got her degree in management information systems and my sister is a biostatistician. Since I was very young I wanted to study mathematics. I enjoyed the rigor and the logic; I loved knowing I had the right answer because I could verify it and prove it to myself. As both an undergraduate and a graduate student this love of mathematics continued to grow. There are so many opportunities for college students in Mathematics. I participated in a couple of Research Experiences for Undergraduates (REUs), where I got to do research in biology and coding theory at different universities. I also studied abroad through Budapest Semesters in Mathematics. I even got to intern at Microsoft Research Asia in Beijing, China. These experiences helped define my career path, and I believe they can do the same for others. Once I graduated, I knew I wanted to do meaningful, impactful work; something that would effect change in a positive way. Sandia National Laboratories was the perfect fit: all the work directly contributes to national and global security. It’s the kind of work that can save people’s lives. Currently at Sandia, I develop algorithms and software for large distributed sensing systems. I use signal and image processing, statistical inference and classification, as well as multiple hypothesis tracking to extract information from sensor data. The project consists of several development teams working to create a single integrated system. My work environment is collaborative; all the members of my team are located together, which invites cooperation and discussion. There are also other teams located in the same area so issues can be addressed quickly and efficiently. 233

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My degree in mathematics has helped me in many ways. It taught me determination and focus – math classes are not easy! It taught me patience and persistence – sometimes you don’t get it on the first try! It taught me problem solving and logic and how to use the tools I have to reach my goals. These are skills that are used and valued in many different jobs and positions. Do I do functional analysis daily? No. Do I apply the fundamental theorem of Galois theory in my day-to-day work? No. But I do use the skills and techniques I learned in these subjects to solve problems every day.

Liz Uribe

Biostatistician Clinical Trials Statistical and Data Management Center (CTSDMC) University of Iowa University of Arizona BS Mathematics University of Iowa MS Biostatistics

I work in clinical trials (these are trials that will test drugs and therapies for safety and efficacy). During a study I run reports on a weekly basis to make sure that the data we have is useable and as complete as we can make it. We also run safety reports looking at adverse events and present these about twice a year to an external data safety monitoring board that makes sure that the trial is safe for the patients involved. At the end of the study, I will write the models necessary to analyze the results and then aid in writing the final report and paper for publication. As a graduate student, I had a research assistantship with one of the heads of the CTSDMC, so when a position opened shortly before I graduated, I jumped at the chance and have been here ever since. I spend a lot of time in front of a computer working with SAS (Statistical Analysis Software) coding up reports or writing models to analyze data. I have a weekly team meeting for each study I’m primary biostatistician on to go over any issues in the study and discuss how to resolve them. If there are any data issues, I may work closely with colleagues to address the issues. Finalizing primary results is also collaborative, as the process entails more than one biostatistician to code up the models for the results. Any differences between them need to be discussed and resolved before results can be presented. My senior year as an undergrad math major I decided I wanted to go to medical school, but it was a bit late for me to take the MCAT and apply to med school right 235

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after graduating. I was planning to take a year to do research, take the MCAT and then go back to school. My math advisor suggested taking two years and getting a masters degree in biostatistics instead. I took his advice and never looked back. As you can probably imagine, there is a lot of math in statistics and biostatistics. Without the solid background in math I had, it would have been even more of a struggle than it was. While we may occasionally have some crunch times, I have rarely had to stay overtime to finish a project or make a deadline. I regularly swim a couple of miles at a nearby lake. Last year I spent January through June training intensely, morning and evening, to swim 40 miles in an event in Arizona called SCAR in April and the Catalina Channel (which is the 21-odd miles from Catalina Island to Los Angeles) in June. One of my fellow co-workers (another biostatistician) and I have slowly been making our way through the Great British Baking Show Masterclass recipes, averaging about one bake a week. I love that this job allows me to have the time to pursue other interests. When I was a student I don’t think biostatistics was available as an undergraduate degree, but I think it is now in some places. If it isn’t at your institution and you want to pursue a career like mine, take probability and statistics courses as an undergraduate. These courses were one of the things I struggled with the most. Get as many research opportunities as you can. Try different ones if it’s possible.

Kim Van Duzer

Second grade teacher Co-Founder of NYC Math Lab New York City Department of Education Columbia College, Columbia University BA English Brooklyn College, City University of New York MS Elementary Education

As a kid, I didn’t realize that math had to make sense. My math teachers instructed me on the procedures required to solve problems, and I diligently repeated those procedures. If I couldn’t easily apply a procedure to the problem I was assigned, I was often stumped. This approach to teaching mathematics is exactly the opposite of what I’ve come to strive for in my work as a teacher of elementary school mathematics. When I graduated college as an English major, I knew that I wanted to teach, but I didn’t expect that mathematics would become my passion. But when I came to teach at PS 29, I began to learn an approach to teaching math in which students investigate mathematical concepts and construct their own understandings of how our number system works. My first year at PS 29 was a true math education for me. I watched in awe as my students discussed and debated, articulately explaining their mathematical thinking. They could approach problems in so many ways, but always with a deeply developed sense of number and operations underlying their work. My fifth graders taught me that doing math involves creativity, communication, attention to structure and precision, use of tools and visual representations, and being part of a mathematical community. After several years of deepening my own knowledge of both the content I was teaching and the math teaching practices that bring out deep understanding, I partnered with two of my colleagues to create the NYC Math Lab. In the summer of July 2015, we spent a week teaching math to a group of rising fifth graders from a local nonprofit’s summer program, while a group of twenty-five teachers observed, analyzed and participated in the teaching. By creating Math Lab we hoped to bring 237

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mathematics teaching practices that encourage students to make sense of concepts to a greater number of students and teachers in New York City. Participating teachers unanimously reported that attending Math Lab was a powerful experience and would impact their own math teaching. Each summer we offer the now-annual NYC Math Lab summer institute. Being able to work with kids and teachers at the same time is one of the unique aspects of Math Lab that I really enjoy. One of my goals as a math teacher is forwarding the belief that math is for everyone. I want kids (and adults) to see that doing math is a joyful, creative and endlessly intriguing pursuit. If you walked into my classroom on a given day, you might see students using unifix cubes to prove that addition is commutative, or coaching each other through solving a problem about the number of tens in 240. (Is it 4? Is it 24? This is a great source of debate for 2nd graders!) If you visited the NYC Math Lab, you might see students using Cuisenaire rods to place fractions on the number line and consider how unit fractions are building blocks for all other fractions. I love being able to uncover the complexity of math concepts some people might view as basic through the eyes of my students. One of the best things about my work is collaborating with so many smart, thoughtful, and dedicated teachers. Classroom teaching is highly engaging, highly collaborative, intellectual work; each student is a new puzzle to be solved (or not), and though of course there are patterns in the way kids learn math and the ideas they have, in sixteen years of teaching, I’ve never once felt bored or like I have it all figured out. If you like working on hard problems, teaching is a great career choice! The best advice I can offer anyone who’s interested in teaching math at any level is not to underestimate the importance of learning how to teach. Knowing the mathematics you’ll be teaching is critically important, but without recognizing all that’s involved in teaching the content well, you won’t get very far. Practicebased teacher education programs that allow for prospective teachers to hone their skills in classrooms, working side by side with experienced teachers and regularly interacting with kids, can help ensure that you’re prepared for the complex work of teaching mathematics. Developing the mathematical understandings of children and teachers, and reshaping their perceptions of math, can be challenging, but it’s extremely rewarding work.

Andrea Walker

Research and Development Manager System Software and Virtualization Sandia National Laboratories Willamette University BA Mathematics University of New Mexico MS Mathematics

I fell in love with mathematics while pursuing a psychology degree at Willamette University. My father was an Electrical Engineer at Sandia National Laboratories and always encouraged and supported my sister and me in math and sciences, so I had a natural aptitude and curiosity for the subject. While pursuing my psychology interests, I continued taking advanced mathematics courses, simply because I was good at it and I enjoyed it. Eventually, while taking a number theory course, I discovered applications of advanced mathematics in interesting fields, like cryptography. At that point, I switched majors and completed my degree, with an interest in becoming a mathematician. I found an internship at Sandia National Laboratories in Albuquerque, New Mexico in the Cryptography department. It was there that I began my career as a researcher – specifically, working in Cryptographic Hardware Assessment as part of the cybersecurity research happening at Sandia. We do cutting edge research for external government partners that has a direct impact on national security. We work on multi-disciplinary teams and solve the world’s hardest technical challenges. My first project as an intern was to help develop SANDstorm, a cryptographic hash function that we submitted as a candidate to the National Institute of Standards and Technology’s Secure Hash Algorithm-3 competition. While working in this job, I completed my master’s degree at the University of New Mexico, studying pure mathematics, in order to deepen my technical mastery of the subject so that I could apply it to the cryptography problems I was working on. After six-and-a-half years as a staff member, I decided to make the career move 239

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into management, and I am now leading the System Software and Virtualization department, still within cybersecurity research. I love my job. It is a challenging, dynamic work environment where you are surrounded by brilliant, amazing, well-rounded people. I love learning and applying my technical skills while also further developing as a leader. My liberal arts background from Willamette has helped me apply not only my skills in mathematics, but also the critical thinking, writing and communication, leadership, and interpersonal skills that are essential for my job. I would encourage future generations of technical students to gain not only extremely deep technical skills in their field, but also a wide array of skills, particularly in leadership, by constantly seeking challenging, unique opportunities. It is also extremely important to love what you do and, for some, to have work-life balance or work-life integration. Sandia’s greatest benefit is our emphasis on the forty-hour work week. This has allowed me to be a student, a wife, and a mom.

Clemmie B. Whatley Associate Professor Mercer University President Educational Dynamix Clark College (now Clark Atlanta University) BA Mathematics Georgia Institute of Technology MS Applied Mathematics Emory University PhD Educational Studies

Growing up in the segregated South and being a part of desegregation during the 1960s and 1970s, I believed I was positioned to trail blaze new careers that were not available to my parents or grandparents. As I completed my undergraduate studies at Clark College, one of my friends, who also majored in mathematics, and I decided we would continue college to complete our Master’s degree in mathematics. We decided that we would attend the same university; hence, when we were both accepted at Georgia Institute of Technology with financial support serving as teacher assistants, we accepted. As trailblazers, my friend and I were the first African American females to complete degrees at Georgia Institute of Technology. I decided to enter the corporate world as an engineer with Southern Bell. (My friend entered the world of programming.) Over the next twenty-two years, I served in various positions at Southern Bell (later known as BellSouth) including engineering, business services, quality assurance, total quality management, human resources, organizational design, and finally reengineering with the restructure of the company. In all of these positions, mathematics was always an integral part of completing the work. For example, when I started as an engineer in depreciation studies, I began to program many of the mathematical processes that were being done manually by my associates. Because of this effort, I was moved to provide central programming support to all the field groups in the depreciation departments located in the Southern Bell states (North Carolina, South Carolina, Georgia, and Florida). I learned much from the corporate experiences but my desire to serve children drew me away from corporate America. While working at BellSouth, I volunteered 241

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to tutor students who needed extra support and I loved being able to make a differences in the lives of students. Therefore, after my two children went to college, I also went back to college to be certified to teach high school mathematics. I taught high school mathematics for four years – always with the plan to continue my education. I attended the University of West Georgia while teaching high school to obtain an educational specialist degree in secondary mathematics and educational leadership. After the fourth year of teaching, when my dear advisement students graduated, I also took a leave to pursue the doctoral degree in Educational Studies from Emory University. What a wonderful time of making a strong connection to the field of education! The background I had developed in the corporate world served me well in education. My associates in different districts began to ask me to help write grants and do evaluations of programs. One of my friends, who was a principal of an elementary school, asked me to help with the implementation of a computer-assisted mathematics program for teachers and students. With these requests and others, the formation of the nonprofit, Educational Dynamix, supporting the educational needs of districts, schools, teachers, students and parents, occurred. Being in schools at the elementary and middle grade levels prompted the development of  Musical Mathematics by Educational Dynamix. Musical Mathematics has been shared with teachers, parents, and students on a national and international level. In 2008, I started as an assistant professor at Mercer University teaching mostly mathematics education courses. More recently, my focus has transitioned to include historical accounts. For example, one of my colleagues at Mercer University and I wrote the book, The Segregated Georgia School for the Deaf: 1882–1975. I am currently working on a book on the Chubb family (my ancestors), who formed a self-sufficient Black community prior to the Civil War. And yes, mathematics is involved in the historical research required for writing. Mathematics has opened many doors for me as I have transitioned from the segregated world of the 50s, 60s, and 70s to the desegregated world we live today. I love to share my experiences and to help others as they decide on their paths – always hoping that the passion for mathematics will help them on their journey.

Beatrice White

Math Teacher Clinton Hill Middle School (Brooklyn Prospect Charter School) Carleton College BA Mathematics Teachers College of Columbia University MA Mathematics Education

A few years ago, I was asked in a parent-teacher conference if it was “too late” for a high school student to pursue math as an interest. In many ways, this question embodies why I have pursued a career in teaching math at the middle and secondary school level. Math opens numerous doors of opportunity, and yet from a relatively young age many students come to believe that they are just not “math people.” High school is too early for a young person to be given the impression that their future with math has already been determined, and as a teacher my hope is to help change students’ minds. My path towards teaching math began while working as a tutor at Carleton College’s Math Skills Center. I was interested in the students who could clearly articulate the “big ideas” of their calculus classes, but who lacked the fluency with algebra to complete their problem sets. At the same time, there were many students who had a solid grasp of the algorithms of algebra, but lacked a conceptual understanding of these foundational skills. For both sets of students, calculus proved difficult, and I wondered how many of them would continue studying math. I wondered, too, about the many students who might never choose to take a class in the math department in the first place. I was just beginning to understand the many skills that contribute to being “good at math” – conceptual understanding, procedural fluency, persistence when taking on novel tasks – and the role that middle and high school education plays in determining who will consider himself/herself a “math person.” 243

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After finishing my undergraduate education, I went on to complete my MA in Math Education and teach in New York as a Math for America fellow. When considering where to work, I have sought out schools with a compelling mission statement that is central to the students’ everyday experience. What constitutes a compelling mission statement will vary from person to person, but for me, I am excited to work in a school that is committed to providing quality education to a diverse student body. In my first year at Brooklyn Prospect Charter School, I worked as a “resident” teacher as opposed to a full-time teaching position. As a resident, I taught a partial load of classes and worked closely with a mentor teacher. This gave me the time and space to learn from the more experienced teachers at my school and to reflect on my own teaching practice. My advice for new teachers, whether a resident-type position is available to you or not, would be to make the time to observe master teachers. Invite others into your classroom to observe and give feedback. Find or create a community of teachers around you to help grow your teaching practice and relationship to your students. Over the last several years, I have taught both middle and high school students at both independent and public charter schools. Currently I am working as a member of the founding team of teachers at the new Clinton Hill Middle School in Brooklyn, NY. I use math every day in the obvious way: much of my time is spent teaching and planning math classes. My background in math helps me to develop a curriculum that fosters a deeper understanding of the underlying mathematical concepts. I also use math in some ways I had not expected before I began teaching. I collect and analyze data about student performance to inform cycles of review and reteaching, and I am also a member of my school’s Math Vision committee, where we plan for the vertical alignment of our curriculum and teaching practices. I am particularly excited about this big picture view of how students experience learning mathematics from kindergarten through twelfth grade. Over time, I have developed a broader understanding of what constitutes “doing math”: in addition to math facts and algorithms, it is my goal to help students become more confident problem solvers and to communicate their own mathematical ideas clearly. I want to develop a classroom community around math where all students feel welcome and able to pursue the subject that I love.

Chris Wiggins Associate Professor Department of Applied Physics and Applied Mathematics Columbia University Chief Data Scientist The New York Times Cofounder hackNY Columbia College BA Physics, Minors in Mathematics and Religion Princeton University PhD Theoretical Physics Currently I’m an associate professor of applied mathematics at Columbia. My research is in machine learning applied to biology. I’m also the Chief Data Scientist at The New York Times, where I’ve been helping them build a data science group, developing and deploying machine learning algorithms to help solve business and newsroom problems. When I was in high school I got very interested in modeling complexity in nature (at the time this was called “chaos”). At the time there was a blossoming of computational research, understanding what complex behaviors could emerge from simple mathematical models. I started doing computational research in high school, then continued at Columbia College, majoring in physics, double minoring in mathematics and religion. One of the most promising places to study complexity in nature at the time was in biology, so I went on to get a PhD in theoretical physics, using continuum mechanical models (mostly PDEs on computers) to model biological physics at the scale of the cell. However, between the time I started and ended my PhD, functional genomics was born thanks to the sequencing of simple organisms and, soon thereafter, humans. It became clear that the scale of data available in biology meant that instead of modeling complexity by looking at simple models producing complex behavior, we could look at abundant data available for complex systems, and try to learn models from these data. We would now call this “data science.” A typical day will involve teaching and meeting with my group, which includes multiple postdoctoral researchers and graduate students. This involves a balance 245

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between talking, writing on the board (sketching a calculation, a model, or how we think a statistical model will perform), and looking at computational results. I’ve long thought that applied mathematics was an audaciously optimistic act: trying to take something as complex as the real world and apply mathematics, the supreme tool for thinking clearly, as a model of that complexity. It’s an exciting time right now when so many fields are enjoying abundant data along with powerful open source statistical tools for making sense of these data. We’ve had a change in tool set for mathematical modeling, along with a change in mindset. A far greater variety of people are interested in modeling and data: those at early career stages as well as those coming from fields of science and industry not traditionally benefiting from mathematical modeling. There has never been a time when people who know how to bring mathematical modeling to complex data could have more direct and diverse impact.

Bryan Williams

Scientist Space and Naval Warfare System Center Atlantic US Navy University of Houston BS Applied Mathematics University of Mississippi MS Mathematics PhD Mathematics

As a naval scientist, I conduct research and lead projects on topic areas of interest to the US Navy. I also have the responsibility of writing proposals to seek external research funding, with the expectation of leading and managing the performance of those projects. I was hired into the Research and Applied Science division of my organization via the Department of Navy Summer Faculty Research program. The program is open to tenure-track Assistant Professors or higher at a US Department of Education accredited institution and allows the faculty member to work shoulder-to-shoulder on naval relevant problems with US Navy scientists and engineers. A normal day for me ranges from conducting basic and applied research on a variety of naval relevant projects to mentoring other scientists and engineers to outlining and identifying future research areas of interest to the US Navy. On average, I work on three to four research or technical management projects per year, so therefore I rarely have the same type of day twice in a row. It is an exciting feeling knowing every day will bring something different. My work environment varies and is dependent upon the project, the scope, and the research area we are currently working in. Some days, in an effort to focus my thoughts on research, I spend some time in solitary. Other times, I work with other scientists and we work collaboratively with other mathematicians, scientists, and engineers on different research topics and subject areas to explore. 247

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When I was looking for a career, there were a number of jobs, programs, and fellowships looking for analytical thinkers and problem solvers. My degree in mathematics helped me to be successful in my career by providing techniques to think about and approach problems. My doctorate is in combinatorics, specifically an area called matroid theory, which can be viewed as a generalization of graph theory or the study of social networks. With an expertise in graph theory, I am able to provide a theoretical analysis of a number of analytics and big data naval relevant projects which require the analysis of very large graphs or social networks. As a government employee, we are highly encouraged to have and are reminded frequently to practice work-life balance. In spite of that, I have still found myself working more than I should be, especially when I find the work very enjoyable. To avoid this, I suggest actively looking for hobbies, taking trips, or just getting out of the house to do something different when you are not working. You do not want to find yourself burning out on your job because you are not allowing your brain enough time to rest. If you are interested in having a job like mine, I would suggest that good grades are very important but they are not the only thing. Internships, fellowships, and community service will help you to become a well-rounded scientist, engineer, or mathematician. Those opportunities will also provide you a diversity of experiences which employers look for when identifying leadership talent. Make sure your professors and your department chair know who you are. Those are the people employers contact to find talent within specific departments. Consider taking classes and learning topics which may be outside of your comfort zone; I guarantee it will pay off because you never know what your future will hold. Finally, choose the right set of friends. If you are hanging around with individuals who are overly negative or like to focus on what they can’t do or what is too hard to do, find some new friends.

Donald C. Williams

CEO Director of Trading and Asset Management Sion Capital, LLC Prairie View A&M University BS Electrical Engineering Purdue University MS Electrical/Computer Engineering Rice University MA Computational and Applied Mathematics

My job involves developing and assessing mathematical models for the valuation and trading of derivative securities, which are general financial instruments that can embody creative structures. For example, consider being able to purchase a “coupon” that would fix the cost you pay per gallon for gasoline for your car. How much would you pay for a coupon that fixes your fuel cost at $2.31 per gallon for three months? Well, if fuel costs are trending upward, it may be a good idea to purchase such a coupon. A further consideration would be, what is the fair price for the coupon? As an example of a financial derivative, the coupon is a way to define one’s financial exposure. The gasoline is the underlying security and the coupon fixes the gasoline price for a fixed period of time. If the price of gasoline goes to $3.25 per gallon, the coupon would be valuable, especially for, say, the shipping industry, where fuel cost directly impacts profit. If, however, gasoline dropped to $1.99 per gallon, the coupon would be worthless. We could actually delve deeper into this fixed price gasoline coupon example, but this is simply a motivating peek into the realm of derivative financial products. Derivative financial products are constructed in various ways to achieve financial exposure. Mathematical models are critically important to quantify financial exposure and assess risk. My daily workflow involves utilizing equity option contracts (a particular type of derivative security) to leverage financial exposure within client portfolios for both profit and risk mitigation. Balancing prescribed financial growth targets with minimizing devaluations or losses along the way is fraught with challenging mathematical questions. Our approach, which uses financial time-series analysis, nonlinear optimization, numerical solutions to differential equations, and 249

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control system analysis, forgoes traditional diversification techniques for the innovative use of statistical metrics and mathematical modeling. The road to my job, as presently defined, was not well paved. Yet, my underlying passion for robotics (control systems), mathematics, problem solving, finance, faith, and family has led me to where I now stand. From my perspective, my job resides at the intersection of electrical engineering, computational science, applied mathematics, and statistics. Contemporary vernacular would employ terms like “financial engineering,” “mathematical finance,” or “computational finance” to characterize various aspects of my daily workflow. The contemporary phraseology is helpful in identifying programmatic areas of study that have emerged and gained recognition over the last twenty years or so, but it does not characterize my path. My passion for finance emerged early in my formative years with my father instilling a strong sense of fiscal responsibility within me during my pre-teen years. He would actually discuss legal rate limits for CD secured loans based on the interest paid on the underlying CD. This may seem like an unusual conversation to have with a kid, but my father was denied loans on a number of occasions because of his race. So, he wanted to inculcate in my brother and me an understanding of saving and self-financing our entrepreneurial endeavors. Although it would take time, study, and experience to process what my father was communicating to me at a young age, he did provide me with my first exposure to structuring financial products to achieve desired outcomes. My passion for finance, however, would take a back seat to electrical engineering and robotics when I began to look into what I would major in for my undergraduate degree. “Financial engineering,” “mathematical finance,” and “computational finance” didn’t exist as degree plans when I matriculated through my undergraduate education. I had no clue about possible careers in finance beyond accounting and traditional banking, which made financial engineering career paths nebulous. My initial academic training and career path took a more traditional route of studying mathematics and earning bachelor’s and master’s degrees in electrical engineering. Working at Los Alamos National Laboratory, first as an intern during undergraduate school and then as a GEM Fellow during graduate school, I found a lot of joy in working on interferometric strain-gauge design and loose-parts dynamical systems for projectile stability. The requisite mathematical and computational demands associated with the work directed my attention towards studying computational and applied mathematics at a deeper level. It was during my graduate work in computational and applied mathematics that I became acquainted with financial engineering as a career path. I worked on developing spread-option pricing models that utilized the mathematical tools of partial differential equations and nonlinear optimization, my core competencies. A typical day of work for me involves waking up with prayer, meditation, and exercise. I’m generally in the office at my desk when US financial markets are open. A third of my time is focused on actively trading and adjusting positions, another third is spent parsing securities for new trading opportunities and running mathematical models that facilitate real-time assessment of trading performance, and the remaining third is spent with research and model development. Time for client communication is integrated into the workflow. Although post-market assessments often occur, my afternoons are committed to the home schooling and spiritual development of our three wonderful boys.

Joyce Yen

Director ADVANCE Program, University of Washington University of Nebraska–Lincoln BS Mathematics University of Michigan MS Industrial and Operations Engineering PhD Industrial and Operations Engineering

A mathematical background is a great springboard for a variety of careers. I was first attracted to mathematics because of the patterns and structure found in foundational subjects. As I explored mathematics more deeply, I came to appreciate how much more there is to mathematics. Indeed, mathematics is a creative field which fosters reasoning and logic skills and encourages tenacity and curiosity. These skills and perspectives come in handy no matter what career path one takes or what problems one encounters. In graduate school, I changed from pure mathematics to operations research, which uses mathematical models to help guide decision making in a wide array of applications (airline crew scheduling, telecommunications network design, breast cancer screening, organ transplant allocation, security detector location, etc.) and uses mathematical insights to improve everyday systems, both complex and simple. It’s a field that has probably touched and improved each of our lives in ways we don’t even realize; for example, getting that online purchase to your door in the most efficient manner possible. After graduate school, I began a career as a professor in Industrial Engineering at the University of Washington (UW) but eventually switched careers. A key motivation for my career change was my interest in the experiences and challenges of women in science and engineering. I decided that I could have a larger impact by working on the issues of women in science and engineering more directly. I am currently the Director of the University of Washington’s ADVANCE Center for Institutional Change. This program, originally created with a grant from 251

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the National Science Foundation, supports the participation and advancement of women faculty in STEM (science, technology, engineering, and mathematics). I design programs, activities, and resources that support faculty professional development and which encourage and advocate a welcoming and supportive academic culture. My personal experiences as a woman in science and engineering provide a valuable perspective. Another aspect of my position is writing proposals to fund new activities and projects whose general aims are to provide resources to faculty and students to foster success in science and engineering and to create an environment in which everyone, and particularly women and people from other underrepresented groups in STEM, can thrive. Through my work with ADVANCE and from my own experience, I believe it’s important for all students, and girls and young women in particular, to know that they can be great mathematicians, scientists, and engineers. Great resources exist to help support you in your success. If you can’t find these resources, keep asking around to find someone who can help you get access to these resources. Women can be and are just as great mathematicians, scientists, and engineers as men. Sometimes, though, women and people from underrepresented groups experience subtle cues that seem to indicate that they do not belong in these fields. We all belong in these fields, and when one has those feelings, it’s important to seek out mentors and other supporters who can and will validate your experiences and your talents. Even with this career change, I still use my mathematical problem solving skills on a daily basis to find creative solutions. Having strong analytical and logical skills is an asset no matter what one’s career is. Moreover, having a technical background allows me to better understand the perspectives and experiences of my primary audiences and helps me more successfully communicate with science and engineering faculty. My mathematical background is an excellent foundation on which to build my career.

Starting your job search Kimberly Betz Executive Director, Career Services Princeton University

One of the most important things for college students to know about conducting a job search is that it takes time. Procrastinating or waiting until after you’ve finished your senior thesis will limit your options, cause unnecessary stress, and quite possibly lead to poor decisions. What does starting early mean? It means beginning to focus on your career development as soon as you begin your first year of college! Self-Exploration. Career development is a lifelong process. It won’t end with your first, fifth, or tenth job. A good way to start is by doing some self-exploration. Spend time reflecting on who you are: what are your interests? Your skills? Your values? While it may sound simple, truly working your way through these questions takes time. Interests. Finding a job that fits with your interests seems like a great idea, right? But how do you know what you’re interested in? Think about past experiences you’ve had – part-time jobs, volunteer work, projects you’ve done for class. Which of these truly captivated you? Positive psychologist Mihaly Csikszentmihalyi talks about the concept of “flow” – a state when you’re so engrossed in what you’re doing that you lose track of time. Write down all the times you’ve experienced this. What themes emerge? If that exercise is challenging for you, you might want to start your investigation of your interests by completing a straightforward interest inventory. Most college career centers offer these – the Strong Interest Inventory is a good example of a tool you can use to start exploring where your interests lie. Skills. In addition to knowing what you like doing, you also need to know what you can do well. Your math classes will give you ample opportunities to hone your quantitative skills. But there may be other skill areas you’re building through your study of math: do you have group projects you work on? These could be building your teamwork skills. Have you ever (formally or informally) tutored someone or explained mathematical concepts? If so, you’re building your communication skills. According to the National Association of Colleges and Employers, some of the top skills valued by employers are: • communication skills 253

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• • • •

teamwork analytical skills problem-solving ability strong work ethic.

These are all skills you’re likely developing in your study of mathematics. Take time to think about which of these skill areas are strongest for you, and then reflect on how you will demonstrate these skills to prospective employers. Values. Have you ever had a job that made you feel anxious, stressed, or even ill? If so, it’s possible that this job did not align with your values. We all want to do work that has meaning for us and makes us feel fulfilled. Reflecting on your top work-related values will help you find a job that you enjoy, feel proud of, and look forward to. Some work values to consider include: helping others, ability to advance, challenge, high financial compensation, independence, and variety of projects. The US Department of Labor’s O*Net website (www.onetonline.org) has a variety of values assessment tools you can use to guide your thinking on what values are most important to you. Learn about what’s possible. Self-assessment is an important part of any job search; but of course, it isn’t sufficient to simply know about yourself. In addition to knowing your interests, skills, and values, you need to know what kinds of jobs exist. Conduct informational interviews. Talking to people to see what they do in their jobs is one of the best ways to learn about what different career fields are really like. Ask your math professors for examples of what their former students are doing now. When you learn about someone who sounds interesting, contact them and ask if you can have an informational interview with them. Informational interviews are much less frightening and more fun than they sound! An informational interview is simply an opportunity for you to ask someone about their job: what they like and dislike, what a typical day is like, what are the challenges, etc. You can even ask for advice on how to successfully apply for jobs in this field. Make use of your career center and your college’s alumni network to identify informational interview prospects. Don’t worry about contacting people – most people like to help, and even enjoy talking about themselves! Look at job postings and attend job fairs. There’s no end to job posting sites on the internet. After you’ve completed some informational interviews and you have some ideas about the types of jobs that might interest you, look at a few of the big job posting sites to search for jobs with titles that interest you. By reading the job descriptions carefully, you’ll get a better idea of whether these jobs might be a good fit for you. You’ll also learn more about the qualifications and credentials you’ll need to be a successful applicant for these types of positions. Another good practice is to attend career fairs – especially those sponsored by your college. Representatives from employers who attend the fairs will be able to give you specific information about the types of positions they typically recruit for, and the skills they look for in new hires. Job fairs are great resources, even for sophomores or juniors, to learn more about jobs they might want to pursue later.

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Get experience – internships are best. You can’t get a job without experience and you can’t get experience without a job. Ever wondered what to do about that catch-22? Internships are the answer! Internships are designed for students who don’t already have professional experience. Look for an internship that will let you test careers you’re interested in and will help you make connections with professionals and build your network. Comic film portrayals of interns who do little more than fetch coffee and unjam the copy machine are thankfully not representative of most internship experiences. The best internships are designed to help you build your skills and provide support for accomplishing your own personal and professional goals. A high-quality internship will equip you with a clear idea of whether or not this career field is one you want to pursue, give you experience to list on your resume, and expand your network of mentors and advisors. It’s important to realize that not all internships are paid, and the ability of organizations to pay interns varies greatly by industry. On average, about half of all internships are paid. Be sure to inquire about wages before accepting an internship. If you find an unpaid internship that would give you great access to learning opportunities, networks, and skill building, inquire whether you can work part-time at the internship, while also working at a paid job. Balancing two commitments can make for a busy summer, but may allow you to achieve both goals of earning money and gaining experience. If you find that your work commitments won’t allow for an additional part-time internship, look into opportunities to volunteer, attend professional events, or even do a day-long job shadow or conduct informational interviews with professionals in fields that interest you. Any exposure you can get to the industry or role you’re considering is beneficial. Network. Many sources say that up to 80% of all jobs are found through networking. This “hidden job market” means that, while searching online for job openings is important, you cannot neglect networking as a critical component of your job search. Luckily for you, you’ve been building your network through informational interviews and internships! Of course, you’ve also built a professional LinkedIn profile, and have been actively linking to your new connections. Keep in touch with people you meet through your career exploration, and let them know when you’re looking for jobs. Use your college’s alumni network, as well as your personal networks, to find people to reach out to. Your career center can help you develop a successful strategy for effective networking. Craft your presentation. As you start to apply for positions, you need to produce impeccably written resumes and cover letters. Your resume should be tailored to the type of position you’re applying for, and must be concise, targeted, and error-free. Each application requires a cover letter written specifically for that particular job. Any document you submit as part of your application must conform to industry standards, and should always be proofread by at least two people. Ask your career center staff, your faculty, and your friends to provide feedback on your documents – and that means planning ahead and allowing plenty of time for critiques and revisions! Be sure, too, to take advantage of resources at your college for practice interviews. Planning your career and searching for jobs can be nerve-wracking. But it can also be exhilarating and rewarding. The job search skills you learn now, along with the networks you build and the reflection and self-assessment you undertake will

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pay off throughout your life as your career shifts and grows. As a college student, your faculty and your career center are fantastic resources – consult with them early and often. And enjoy the adventure!

Preparing for an interview

Kimberly Betz Executive Director, Career Services Princeton University

Congratulations – you’ve been invited for an interview! An interview is an exciting part of the job search process, and an opportunity to showcase your skills and experiences. It’s also an opportunity to meet prospective co-workers and learn more about whether this employer and position is one that would be a good fit for you. Now that you’re going to an interview, what do you need to do to be prepared to make a great impression? Clarify logistics. If your interview invitation doesn’t already articulate this information, be sure to inquire. • How long will the interview be? Will you be meeting with multiple people? Who will you be meeting with? • If you’re driving to the interview, where should you park? Do you need a parking permit? • If you’re traveling a longer distance, who will pay for travel expenses? Will the employer provide travel expenses, or are you expected to pay your own way? Do your research. You’ve already researched the organization to write a targeted resume and cover letter. Now it’s time to do deeper research. You need to learn everything you can about the organization and the job before you show up for your interview. One of interviewers’ biggest pet peeves is when candidates lack basic information about the organization. Of course, the easiest way to learn about how an organization views itself is by carefully reading its website. Of course, you’ll also thoroughly study the job description, and look for clues about the types of skills and experiences they’ll be screening for in the interview. In addition to these direct methods of researching the organization, there are many additional ways to learn more. • Read industry publications. For example, if you’re applying for a position in marketing analytics at an advertising agency, you should read the past few issues of Advertising Age and Ad Week. • Keep up with the news. At a minimum, do a Google news search on the organization and industry to learn about major events or trends. 257

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• Search for insights on employee review sites. Sites such as Glassdoor (glassdoor.com) can give you insider information and perspectives from current and former employees. • Use your network. Now is the time to make use of that network of professional contacts you’ve been building. If you don’t already know people who work at the organization you’re interviewing with, use your college’s alumni directory. Ask your contact for a few minutes of their time for a phone call, and get their advice on how you can best position yourself to be successful in your interview with this particular organization. • LinkedIn profiles. Do your research on the individuals with whom you’ll be meeting. This will give you an idea of how long they’ve been with the organization, where they worked before coming here, and what their areas of specialization are. Review your resume. It may sound silly, but take time to thoroughly review your resume as you prepare for your interview. Anything that you’ve included on your resume is fair game for questions at an interview. If you wrote about a project you worked on for a class you took a few years ago, be sure that you can recall details of the project. Think about stories you could tell about any of the items you’ve included on your resume. For example, be ready to talk about challenges and accomplishments for any of the summer jobs, volunteer experiences, or internships you’ve listed. If you’ve listed any special skills on your resume, be sure you can give examples of when and how you’ve used them. Prepare for common interview questions. Like it or not, there’s a set of common interview questions for which you should prepare. These are the questions many of us dread. Preparing answers to these questions ahead of time will serve you well. And as with any interview preparation, practice makes perfect! It can be helpful to write out your answers to these questions, and then practice role-playing them with friends until you feel comfortable with your answers. • Tell me about yourself. (Not really a question, but a common interview opener.) Make your answer concise and relevant to the position you’re interviewing for. • What are your strengths and weaknesses? Don’t try to be cute (e.g. “My greatest weakness is chocolate.”) Think of an actual weakness, and then describe ways you’ve worked to improve it. If you’re having trouble thinking of strengths, ask your friends for suggestions. • Why do you want to work here, and why do you want this job? This is where your research will pay off! • Where do you see yourself in five years? You may not know the answer to this question, but think of an option that might be possible – and make sure it corresponds to something that would be feasible if you were to accept this job. Again, don’t try to be cute (e.g. “In five years, I see myself having your job.”). Prepare for behavioral-based questions. Behavioral interviewing is common in many industries. The theory behind this type of question is that past behavior predicts future behavior. These questions usually take the form of “Tell me about a time when...” or “Give me an example of...” When answering these questions, take pains to use a specific example. One of the common mistakes made

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in answering these questions is to use generalities. Resist starting your answers with “Usually, when this type of situation comes up...” Remember, they asked you for a specific example. A good strategy for structuring answers to behavioral-based questions is to use the STAR method (Situation, Task, Action, Result). Consider this example: “Tell me about a time when you had to work with a team to accomplish an assignment.” Situation: “I was taking an advanced statistical modeling class.” Task: “I was assigned to work with a group of five other students to consult with our athletics department and analyze results from last season.” Action: “We set up a list of tasks and divided responsibilities.” Here’s where you get to the meat of what you did. Result: “We presented our results to the athletic director, who has begun using our work to create a strategy for next season. And we received an A for our work in the class.” Don’t forget to end your answer by giving the results. Although this is probably the most important part of your answer, it’s also the part most commonly forgotten by interviewees. Prepare for “What questions do you have for me?” Nearly every interview ends with this question. This is a great opportunity for you to get more detailed information about the position and the organization. It’s expected that you should have questions – if you truly don’t have questions, your interviewer is likely to assume that you’re not really all that interested in the position. Prepare a lot of questions to ask. Write a list of 10-15 questions to take with you to the interview. Of course, you won’t have an opportunity to ask that many questions, but you need to plan ahead, so that you still have questions left to ask if some of them get answered through the course of the interview. Note that this is not the time to ask about salary – that question, if it hasn’t already been answered, needs to wait until you have a job offer on the table. Practice! This should come as no surprise. Interviewing is a skill like any other – it gets better with practice. The construct of an interview is awkward – talking about yourself doesn’t come naturally to most of us. The more you practice, the easier this will become. Your college career center is a great resource for practice interviews. If they offer the option to record your practice interview, do it! It’s probably going to feel uncomfortable to have the camera pointed at you as you answer the questions, but after going through that experience, the actual interview will feel much less awkward and intimidating! Do special prep for special interviews. Certain industries have unique styles of interviews. If you’re interviewing for a tech position, you need to be prepared for a coding interview. Consulting and finance positions frequently conduct case interviews. These styles of interviews call for special preparation and even more intensive practice. Consult with your college career center for advice on how to prepare for these types of interviews. Review the basics. • Prepare, research, and practice. Probably the most important thing you can do to prepare for an interview is practice. Practice, get feedback, and then practice some more.

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• Get rest. You’re probably juggling lots of commitments and assignments, and an interview is one more thing to add to the list. But it’s critical that you budget your time wisely and get a good night’s sleep before your interview. You’ll need to be at your best for your interview, and you can’t do that if you’re running on fumes. • Dress appropriately. You can’t go wrong wearing a suit to an interview. Even if you’re interviewing at an organization that has a very casual culture, wearing a suit shows that you’re taking this interview seriously, that you respect the interviewer, and that you can be seen as a professional. • Arrive early. Make sure you’ve got the logistics planned in advance, so that you can be in the waiting room 10 minutes early. It doesn’t hurt to arrive at the site even a bit earlier than that, to give yourself time to use the restroom, find the right office, etc. • Bring a copy of your resume and application materials. It’s likely that your interviewer will have all of this already, but it doesn’t hurt to have an extra copy, just to be prepared. • Be polite and attentive to everyone. From the minute you arrive at the interview site, you’re being evaluated. Everyone from the security guard to the receptionist to the interns may be asked to provide feedback on you. Make a good impression on everyone you meet. • Send a thank-you. As soon as you’ve finished the interview, make a point to write a sincere and personalized thank-you to everyone who participated in your interview. Email is a fine way to do this. Most important is that you are prompt and sincere in your message. With practice and preparation, interviews can be a pleasant experience, and an opportunity for you to evaluate your prospective employer as much as they’re evaluating you. Interviewing is a skill you’ll use throughout your life, so start strong and use the resources available to you at your college to hone your skills and become an interviewing expert.

Applying to graduate school Gabriela Pineider, MEd Career Consultant College of Science and Engineering Texas Christian University

Every college student remembers the process they went through to apply to their undergraduate institution: the endless applications, the campus visits, the standardized tests. Though the process is often associated with anxiety, the payoff is worthwhile when you finish your degree and are one step closer to your dream career. Toward the end of your bachelor’s degree, however, you may begin to consider going to graduate school. How do you know if graduate school is for you? The decision of whether or not to pursue graduate study is something that will impact the next two or more years of your life, both financially and emotionally. This is an important decision and should be given serious thought. Graduate study will typically involve intensive coursework and/or research, and gauging your passion for research can help you decide if graduate school is right for you. Graduate research presents unique challenges, so seek out a research experience as an undergraduate to decide how much you enjoy doing research. A summer REU (Research Experience for Undergraduates), an internship at a National Laboratory, or an appointment as a research assistant to a faculty member at your school are great ways to get this taste of research. Burnout is common at the end of an undergraduate career, so don’t be afraid to take a break if you’re not really sure if you have the academic stamina to begin again. If you are considering graduate school because it will allow you to postpone the “real world” a while longer, that will not give you the energy to make graduate school a positive experience; you need a good reason to go to graduate school. In some cases, employers will pay for new employees to continue their education, so if you are having trouble deciding whether to go into an industry job or graduate school, research this option. If a potential employer will allow you to go to school part time and assist with the cost, it could be the best of both worlds in the sense that you continue to develop both professionally and academically. It is also important to remember that graduate school will mean additional stress for the foreseeable future. Similar to your time as an undergraduate, you have to consider if it is a good stress or a negative stress. If the subject matter of the program you are considering is something you are passionate and curious about, the stress can be the positive kind that drives you to complete those assignments, dig into 261

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your research, and excel in your classes. If you are unsure of your decision, meet with someone in your Career Development office. They should be able to talk to you more about the careers you are considering and if graduate school is necessary and a benefit to your professional growth. Your Career Development office has a wealth of knowledge that can help you find your best-fitting career path and your best-fitting graduate program. Where to apply. A number of factors go into your decision about where to apply: do you want to be in a prestigious program which is perhaps more competitive and has a lower graduation rate, or would you rather be in a supportive environment with a higher rate of completion? Do you want to be in a large graduate program with 150-200 graduate students where you can maintain some anonymity, or a small program with 40 graduate students and the professors know your name? Do you want to be in a program that prides itself on inclusivity and diversity, or does that not matter to you? Do you have particular subject matter you know you will want to study, so you need to be sure that is available where you apply, or would you prefer a large program with many options because you’re not sure of your interests? Once you know some of these answers, go talk to your advisors and faculty in your department because they know you best. Graduate school admissions can also be competitive. It is important to be honest with yourself in terms of your qualifications for the programs you are considering. How hard are you willing to study? How determined are you to finish? How are your grades as an undergraduate? Do you have the time to invest in your application materials? Ideally, you should do your research into where you’d like to apply and the application deadlines during your junior year of college. Applying to graduate school. Once you know where you want to apply, find out what entrance exams they require. Applying to graduate school often requires standardized testing in the form of the LSAT or GMAT or general GRE; in mathematics, the general GRE is usually required and the math subject GRE is sometimes required. These are not tests that you should take lightly. You need to make sure that you are able and willing to give yourself ample time to prepare, whether it is with practice tests, prep books, prep tutors, or classes. While the general GRE is offered frequently, the math subject GRE is not. Some graduate degree programs have deadlines at the end of fall semester of your senior year, so it’s generally a good idea to take the GRE Math in the spring of your junior year so that you can have an opportunity to retake in the fall of your senior year if you wish. Check out the ETS website (http://www.ets.org) for dates. When applying to graduate school, there are a number of moving parts to stay on top of. Organization can be key to keeping track of everything. In the Center for Career and Professional Development at Texas Christian University, we provide students with a spreadsheet where students can organize all of their information: schools applying to, fee to apply, deadline, website used to apply, tests required, fee to take test, additional materials. By keeping track of this information, students are able to stay on top of deadlines and check things off as they complete them. There are many pieces to a complete application, so work well in advance of the deadlines. The majority of applications are completed online, but we all know that technology can be unreliable. Therefore, make sure that you are not submitting your application on the final day during the final hour before the deadline because

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if something glitches or gives you trouble, you want to make sure you have sufficient time to call the institution or troubleshoot what happened. If the application does require that you physically mail any information, it is important to verify if the materials have to be postmarked by the deadline or received by the institution on the deadline. This can impact whether your application is considered complete. Additionally, when asking your faculty, REU (research experience for undergraduates) advisors, or previous supervisors for recommendations, it is crucial that you give them ample time to not only write the letter, but also to mail or submit the letter. Be courteous to your recommender by preparing a single written list of all letters of recommendation that you are requesting, including name of institution, deadline, directions for submission, and any other information your recommender will need. It’s also useful to remind them which terms you took which classes with them, did research with them, or were their grader. One of the biggest components to applying to graduate school is writing the personal statement. Some schools will provide a specific prompt, others may keep it general and simply ask that you describe why you would like to attend their program. It is important that you have clearly understood their requirements such as prompt, word/character count and format for submission. When writing your personal statement you want to stay focused on what has driven you to pursue the program you are applying to, what makes you a good candidate (using specific examples), and explaining why that school in particular is the best one for you. If you have had experience doing research on your own or with a team, describe the project and your experience doing research. By accepting you into their graduate program, the university is making an investment in you, as well; they want to know that you’re someone who will make the most of the opportunity. Lastly, make sure you find a reliable source(s) to review your statement, potentially multiple times. Your undergraduate institution’s Career Center should be able to give you a review as well as one of your mentors or recommenders. Having a second (and third) set of eyes read through your personal statement will help you get a fresh perspective, verify important factors such as grammar and spelling while also providing an opinion on your statement. After you’ve applied, you may get invitations to visit some graduate schools. Oftentimes, students spend a great deal of time visiting schools for their undergraduate degree, but fewer students take the time to visit schools they are considering for graduate school. Visiting a graduate program can be a very telling indication of whether the program, material, and culture are a good fit. Graduate programs are naturally smaller than undergraduate programs. This means you will have repeated interactions with the same faculty, staff, and peers. As a result, meeting them will allow you to learn more about the program and the opportunities afforded to the students who attend. If you are unable to visit graduate schools, look up the names of some of the graduate students in the programs to which you applied, and send them an email with questions about their experiences in that graduate program. How is the teaching? Do they like their colleagues? Is it a friendly or competitive environment? What percentage of students who start graduate school finish a degree? The benefits of going to graduate school. In 2017, Jeffrey Selingo wrote an article, referring to data from the National Bureau of Economic Research, stating that in the 1980’s the bachelor’s degree was the ticket to higher paying jobs and

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access to new opportunities. While that has held true in the last 30 years, we are seeing a shift. A higher percentage of people have bachelor’s degree now, and, as a result, graduate school has become part of the conversation. In some industries, getting a master’s degree or doctoral degree is the ticket to those higher-paying, upper-level opportunities and promotions. Additionally, you are provided access to those advanced opportunities sooner in your career than if you wait to attend graduate school years into your career when younger candidates, who went straight through graduate after their bachelor’s degree, are moving into upper-level positions at a faster rate than you. If you go to graduate school immediately after your bachelor’s degree, you also are in the habit of studying and your knowledge from undergrad is fresh. Some graduate programs, such as in data science, also provide opportunities such as working on industrial research under faculty members. This is a great resume builder and will help any candidate in applying for industry jobs. Many students know networking is a vital part of the career advancement process. What students do not often realize is that graduate programs provide easier access to networking opportunities. Many faculty members have personal connections to people who can help their students advance in their careers. This is especially useful to the students who wouldn’t otherwise know how to “get out there” and meet employers. Additionally, being in graduate school provides you continued access to resources like your school’s career center, where you can have your resume reviewed and receive tips for networking so you are prepared when the employers come to campus. Ultimately, deciding whether or not to go to graduate school is a very personal process, but it can be simplified by taking advantage of the resources you have within your career center staff, your faculty and other mentors. As you develop questions, get them answered and do not be afraid to explore the options; it is never too soon. Regardless of the path you chose, just remember that life after your bachelor’s degree is a great journey and embracing the change will lead to your greatest accomplishments.

Contents by career area Academia and Nonprofit Charlotte Abrams MPH Biostatistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Graduate Student, Columbia University Ben Baumer PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Assistant Professor, Smith College; Statistical Analyst, NY Mets Stacy Beaudoin MST Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Math Teacher, St. Paul’s School Jenna Carpenter PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Founding Dean and Professor, Campbell University Tim Chartier PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Professor, Mathematics and Computer Science, Davidson College Mimi Cukier BA Mathematics and Philosophy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Mathematics Teacher, The Park School of Baltimore Joshua R. Davis PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Lecturer in Mathematics, Statistics, and Computer Science, Carleton College Katie Evans PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Professor of Mathematics and Statistics, Louisiana Tech University Tamara Fuenzalida MS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Instructor of Mathematics, Tarrant County College Northeast Angela Gallant MS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Mathematics Instructor, Inver Hills College Sommer Gentry PhD Electrical Engineering and Computer Science . . . . . . . . 77 Mathematics Professor, US Naval Academy Amanda (Quiring) Gonzales PhD Business Administration (Accounting) . 81 Assistant Professor of Accounting, University of Nebraska Lincoln Amanda Hanford PhD Acoustics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Assistant Research Professor in Acoustics, The Pennsylvania State University Ebony Hitch BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .87 Mathematics Teacher, Wicomico High School David Keyes PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Senior Program Manager, IXL Learning George Mohler PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Associate Professor, Indiana University-Purdue University Indianapolis Tanya Moore PhD Biostatistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 VP, Mission Advancement, Goodwill of San Francisco, San Mateo, and Marin Christine Papai MS Mathematics, MDP International Development . . . . . . 161 Deputy Country Director, Innovations for Poverty Action Ghana 265

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Yolanda Parker PhD Mathematics Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 Mathematics Professor, Tarrant County College Elizabeth Pontius MD Medicine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 Attending Physician, MedStar Washington Hospital Center Shannon Rogers BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Curriculum Developer, Art of Problem Solving Kayli Schafer BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 Enterprise Strategy Manager, OneAmerica Rebecca Swanson PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Teaching Professor, Colorado School of Mines Alec Torigian Master of Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .227 Associate Director, Alliance for Catholic Education Teaching Fellows Kim Van Duzer MS Elementary Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 Teacher, Co-Founder of NYC Math Lab, NYC Department of Education Clemmie B. Whatley PhD Educational Studies . . . . . . . . . . . . . . . . . . . . . . . . . . 241 Associate Professor, Mercer University; President, Educational Dynamix Beatrice White MA Mathematics Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243 Math Teacher, Clinton Hill Middle School Chris Wiggins PhD Theoretical Physics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 Associate Professor, Columbia University; Chief Data Scientist, The NY Times Joyce Yen PhD Industrial and Operations Engineering . . . . . . . . . . . . . . . . . . . . 251 Director, ADVANCE Program, University of Washington

Actuarial Science and Accounting Amanda (Quiring) Gonzales PhD Business Administration (Accounting) . 81 Assistant Professor of Accounting, University of Nebraska Lincoln Kimberly Plesnicar MS Actuarial Science . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Actuarial Analyst II, Zurich North America Rachel Ramirez BA Mathematics with Actuarial Science Concentration . . . 183 Actuarial Analyst, National Life Group Adam Rich BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 Actuary, Head of Specialty Lines Analytics, Beazley Group PLC Christina Roberts BA Mathematics and Spanish . . . . . . . . . . . . . . . . . . . . . . . . . 191 Assistant VP, Senior Catastrophe Modeling Analyst, Validus Reinsurance

Business Management Brian T. Bares BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Founder and Chief Investment Officer, Bares Capital Management, Inc. Paige Bartholomew BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Consultant, Bain & Company Marina Brockway PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Chief Technology Officer and Founder, VivaQuant Jaquelyn Fernandez Rieke BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Founder, Nutty Steph’s; Land Steward, Onion River Campground Kathie Flood MA Journalism and Mass Communications . . . . . . . . . . . . . . . . . . 69 CEO, Cascade Game Foundry SPC

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Jennika Gold Thomas MS Computational Finance, MS Mathematics . . . . . . 79 Director of Strategy, Fixed Income Analytics, FactSet Harold Hausman BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Owner and Senior Software Engineer, TechAscent Erin Jones BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Go-To-Market and Sales Strategy Manager, RSA, Dell Technologies Tanya Moore PhD Biostatistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 VP, Mission Advancement, Goodwill of San Francisco, San Mateo, and Marin Laurel Paget-Seekins PhD Civil Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 Director of Strategic Initiatives, Massachusetts Bay Transportation Authority Cara D. Petonic MBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .167 Director, Corporate Strategy, Comcast Corporation Jeffrey Saltzman PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Proprietor, Cottonwood Applied Mathematics Benjamin P. Simmons BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213 Vice President, Risk Solutions, Gravie Courtney Stephens BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 CEO, QED Energy Associates Shree Taylor PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 President and CEO, Delta Decisions of DC, LLC Jane Turnbull MS Applied Probability and Statistics . . . . . . . . . . . . . . . . . . . . . . 231 Assistant Vice President, Equifax Clemmie B. Whatley PhD Educational Studies . . . . . . . . . . . . . . . . . . . . . . . . . . 241 Associate Professor, Mercer University; President, Educational Dynamix Chris Wiggins PhD Theoretical Physics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 Associate Professor, Columbia University; Chief Data Scientist, The NY Times Donald C. Williams MA Computational and Applied Mathematics . . . . . . . 249 CEO, Director of Trading and Asset Management, Sion Capital, LLC

Computing, Software Design, and Cyber Security Nicole Bertram MS Cellular and Molecular Biology . . . . . . . . . . . . . . . . . . . . . . . . 21 Software Developer, Epic Systems Corporation Marina Brockway PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Chief Technology Officer and Founder, VivaQuant Sarah Brown MA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Senior Scientist, NATO Communications and Information Agency Carla Cotwright-Williams PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Computer Scientist, Hardy-Apfel IT Fellow, US Social Security Administration Kathleen Daly BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Staff Engineer, Booz Allen Hamilton Joshua R. Davis PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Lecturer in Mathematics, Statistics, and Computer Science, Carleton College Erick Deras BA Mathematics and Computer Science . . . . . . . . . . . . . . . . . . . . . . . 49 Lead Software Development Engineer, The Rubicon Project Chandra Erdman PhD Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 Senior Solutions Consultant, Google, Inc.

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Kathie Flood MA Journalism and Mass Communications . . . . . . . . . . . . . . . . . . 69 CEO, Cascade Game Foundry SPC Harold Hausman BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Owner and Senior Software Engineer, TechAscent Kelly Hobson BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 Software Tester, Internet of Things Solution, SAS Institute Maribeth Johnson BA Mathematics and Neuroscience . . . . . . . . . . . . . . . . . . . . .99 Boost Consultant, Epic Systems Corporation Harlan Kadish PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Field Software Engineer, Tamr Inc. David Keyes PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Senior Program Manager, IXL Learning Alex McAdams PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Senior Software Engineer, Walt Disney Animation Studios Janeth Moran-Cervantes MS Computer Science . . . . . . . . . . . . . . . . . . . . . . . . . 139 Software Development Engineer, Amazon Carol Muehrcke PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 Independent Cyber Security Consultant Grace Nabholz BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Research Mathematician, US Army Corps of Engineers Karoline Pershell PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 Lead Technical Researcher, Zenti, Inc. Jacqueline Pfadt MBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Technical Lead, Savantage Solution Amanda Plunkett PhD Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .175 Analytic Team Lead, Department of Defense Blake Rector PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 Director of Analytics, Powin Energy Lucas Sabalka PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 Computer Vision Specialist, Ocuvera, LLC Jasmin Uribe MS Applied Mathematics, MS Computer Science . . . . . . . . . . . 233 Research and Development Computer Scientist, Sandia National Laboratories

Consulting Xiaoling (Ling Ling) Lim Ang PhD Economics . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Associate Director, NERA Economic Consulting Paige Bartholomew BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Consultant, Bain & Company Chandra Erdman PhD Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 Senior Solutions Consultant, Google, Inc. CJ Jaynes MS Mathematics, MBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Rear Admiral (ret), US Navy; Executive Technical Advisor, Raytheon Company Maribeth Johnson BA Mathematics and Neuroscience . . . . . . . . . . . . . . . . . . . . .99 Boost Consultant, Epic Systems Corporation Carol Muehrcke PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 Independent Cyber Security Consultant

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Jeffrey Saltzman PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Proprietor, Cottonwood Applied Mathematics Courtney Stephens BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 CEO, QED Energy Associates Shree Taylor PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 President and CEO, Delta Decisions of DC, LLC

Data Analytics Ben Baumer PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Assistant Professor, Smith College; Statistical Analyst, NY Mets Ebonii Bell MA Computational and Applied Mathematics . . . . . . . . . . . . . . . . . . 15 Senior Supply Chain Analyst, Abbott Robert M. Bell PhD Mathematical Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Statistician (retired), RAND, AT&T, and Google, Inc. Lisa Byrne MS Mathematics and Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Data Scientist, WeddingWire Tim Chartier PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Professor, Mathematics and Computer Science, Davidson College Carla Cotwright-Williams PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Computer Scientist, Hardy-Apfel IT Fellow, US Social Security Administration Michael Dairyko PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Senior Manager – Data Scientist, Milwaukee Brewers Erick Deras BA Mathematics and Computer Science . . . . . . . . . . . . . . . . . . . . . . . 49 Lead Software Development Engineer, The Rubicon Project Samantha Drost BS Mathematics, BA Economics . . . . . . . . . . . . . . . . . . . . . . . . . 55 Senior Analyst, Business Intelligence and Analytics, Target Corporation Berton Earnshaw PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Director, Data Science Research, Recursion Pharmaceuticals Chandra Erdman PhD Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 Senior Solutions Consultant, Google, Inc. Stephanie Fitchett PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Statistician and Data Scientist, Transamerica Life Insurance Company Jennika Gold Thomas MS Computational Finance, MS Mathematics . . . . . . 79 Director of Strategy, Fixed Income Analytics, FactSet Rachel Insoft BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Senior Analyst, Quantitative Economics and Statistics Group, Ernst & Young Eleisha Jackson PhD Ecology, Evolution, and Behavior . . . . . . . . . . . . . . . . . . . . 95 Data Scientist, Livongo Stacey Faulkenberg Larsen PhD Mathematical Statistics . . . . . . . . . . . . . . . . 111 Lead Analyst, Business Intelligence and Analytics, Target Corporation George Mohler PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Associate Professor, Indiana University-Purdue University Indianapolis David Moore MS Environmental Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Environmental Products Analyst, Element Markets Jacqueline Nolis PhD Industrial Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Director of Analytics, Marketing and Sales Strategy Firm

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Kyle Novak PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Deputy Chief Analyst, US Air Force (retired) Dean Oliver PhD Environmental Science and Engineering . . . . . . . . . . . . . . . . .157 Vice President of Data Science, TruMedia Networks Laurel Paget-Seekins PhD Civil Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 Director of Strategic Initiatives, Massachusetts Bay Transportation Authority Ashley Pitlyk PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Senior Data Scientist, Care Otter Amanda Plunkett PhD Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .175 Analytic Team Lead, Department of Defense Emilie Purvine PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Data Scientist, Pacific Northwest National Laboratory Blake Rector PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 Director of Analytics, Powin Energy Christina Roberts BA Mathematics and Spanish . . . . . . . . . . . . . . . . . . . . . . . . . 191 Assistant VP, Senior Catastrophe Modeling Analyst, Validus Reinsurance Ali Shappy MBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 Inventory Analyst, The Vermont Country Store Richard Sharp PhD Applied and Computational Mathematics . . . . . . . . . . . . . 209 Data Scientist, Starbucks Danielle Shepherd BA Mathematics and Physics . . . . . . . . . . . . . . . . . . . . . . . . . 211 Simulation Engineer, Chip Ganassi Racing Jean Steiner PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217 Senior Director of Data and Insights, Skillshare Sumanth Swaminathan PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . 221 Chief Data Scientist, Revon Systems Inc Shree Taylor PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 President and CEO, Delta Decisions of DC, LLC Chris Wiggins PhD Theoretical Physics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 Associate Professor, Columbia University; Chief Data Scientist, The NY Times

Economics, Finance, and Investment Analysis Xiaoling (Ling Ling) Lim Ang PhD Economics . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Associate Director, NERA Economic Consulting Noelle Balandi MS Financial Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Finance Specialist, Multnomah County, Oregon Brian T. Bares BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Founder and Chief Investment Officer, Bares Capital Management, Inc. Rachel Insoft BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Senior Analyst, Quantitative Economics and Statistics Group, Ernst & Young Marina Johnson BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Analyst, Morgan Stanley Barbara Jordan BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Assistant Vice President, Credit Risk Management, GM Financial Dan Loeb PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Quantitative Research Analyst, Susquehanna International Group

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Christopher Minck BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Fixed Income Trader, BlackRock Andy Niedermaier PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 Trader, Jane Street Capital Jane Turnbull MS Applied Probability and Statistics . . . . . . . . . . . . . . . . . . . . . . 231 Assistant Vice President, Equifax Donald C. Williams MA Computational and Applied Mathematics . . . . . . . 249 CEO, Director of Trading and Asset Management, Sion Capital, LLC

Energy Nicholas Bennett PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Research Scientist, Schlumberger David Moore MS Environmental Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Environmental Products Analyst, Element Markets Walter Morales MS Petroleum Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 Technologist, Chevron Corporation Blake Rector PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 Director of Analytics, Powin Energy Courtney Stephens BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 CEO, QED Energy Associates

Engineering and Law Jenna Carpenter PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Founding Dean and Professor, Campbell University Kathleen Daly BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Staff Engineer, Booz Allen Hamilton Alyson Doles BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Research Mathematician, US Army Corps of Engineers Kate Dyson Juris Doctor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Partner, White & Case LLP Katie Evans PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Professor of Mathematics and Statistics, Louisiana Tech University CJ Jaynes MS Mathematics, MBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Rear Admiral (ret), US Navy; Executive Technical Advisor, Raytheon Company Danielle Shepherd BA Mathematics and Physics . . . . . . . . . . . . . . . . . . . . . . . . . 211 Simulation Engineer, Chip Ganassi Racing

Government and Military Noelle Balandi MS Financial Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Finance Specialist, Multnomah County, Oregon Toni Bluher PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Subject Matter Expert in Cryptography, National Security Agency Kate Brady MA Urban and Environmental Planning . . . . . . . . . . . . . . . . . . . . . . . 25 Senior Bicycle Planner, City of Colorado Springs Sarah Brown MA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Senior Scientist, NATO Communications and Information Agency

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Carla Cotwright-Williams PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Computer Scientist, Hardy-Apfel IT Fellow, US Social Security Administration Alyson Doles BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Research Mathematician, US Army Corps of Engineers Skip Garibaldi PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Director, IDA Center for Communications Research Sommer Gentry PhD Electrical Engineering and Computer Science . . . . . . . . 77 Mathematics Professor, US Naval Academy Amanda Hanford PhD Acoustics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Assistant Research Professor in Acoustics, The Pennsylvania State University Marylesa Howard PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 Senior Scientist, Nevada National Security Site CJ Jaynes MS Mathematics, MBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Rear Admiral (ret), US Navy; Executive Technical Advisor, Raytheon Company Aaron Luttman PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Principal Scientist, Nevada National Security Site Chad Magers MS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Scientist, Naval Surface Warfare Center Carol Meyers PhD Operations Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 Mathematician and Project Manager, Lawrence Livermore National Laboratory Grace Nabholz BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Research Mathematician, US Army Corps of Engineers Aisha N´ ajera Chesler PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . 147 Associate Mathematician, RAND Corporation Kyle Novak PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Deputy Chief Analyst, US Air Force (retired) Laurel Paget-Seekins PhD Civil Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 Director of Strategic Initiatives, Massachusetts Bay Transportation Authority Amanda Plunkett PhD Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .175 Analytic Team Lead, Department of Defense Emilie Purvine PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Data Scientist, Pacific Northwest National Laboratory Mary Lynn Reed PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 Chief, Mathematics Research Group, National Security Agency Bonita Saunders PhD Computational and Applied Mathematics . . . . . . . . . . 199 Mathematician, National Institute of Standards and Technology Jeanette Shakalli PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 Exec Asst, National Secretariat of Science, Technology & Innovation, Panama Robert Troy BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 Pilot, US Air Force Jasmin Uribe MS Applied Mathematics, MS Computer Science . . . . . . . . . . . 233 Research and Development Computer Scientist, Sandia National Laboratories Andrea Walker MS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 Research and Development Manager, Sandia National Laboratories Bryan Williams PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 Scientist, Space and Naval Warfare System Center Atlantic, US Navy

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Healthcare and Medicine Nicole Bertram MS Cellular and Molecular Biology . . . . . . . . . . . . . . . . . . . . . . . . 21 Software Developer, Epic Systems Corporation Marina Brockway PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Chief Technology Officer and Founder, VivaQuant Lizette Ortega Dickey MS Biostatistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 Biostatistician, Contract Research Organization Berton Earnshaw PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Director, Data Science Research, Recursion Pharmaceuticals Stephanie Fitchett PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Statistician and Data Scientist, Transamerica Life Insurance Company Sommer Gentry PhD Electrical Engineering and Computer Science . . . . . . . . 77 Mathematics Professor, US Naval Academy Maribeth Johnson BA Mathematics and Neuroscience . . . . . . . . . . . . . . . . . . . . .99 Boost Consultant, Epic Systems Corporation Erika Meza MPH Environmental Health Sciences . . . . . . . . . . . . . . . . . . . . . . . . . 127 Project Associate, The RAND Corporation Christine Papai MS Mathematics, MDP International Development . . . . . . 161 Deputy Country Director, Innovations for Poverty Action Ghana Ashley Pitlyk PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Senior Data Scientist, Care Otter Elizabeth Pontius MD Medicine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 Attending Physician, MedStar Washington Hospital Center Lucas Sabalka PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 Computer Vision Specialist, Ocuvera, LLC Benjamin P. Simmons BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213 Vice President, Risk Solutions, Gravie Andrew Stein PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215 Associate Director of Pharmacometrics, Novartis Sumanth Swaminathan PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . 221 Chief Data Scientist, Revon Systems Inc Liz Uribe MS Biostatistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 Biostatistician, University of Iowa

Research Nicholas Bennett PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Research Scientist, Schlumberger Toni Bluher PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Subject Matter Expert in Cryptography, National Security Agency Bill Correll, Jr. PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Research Scientist, Radiant Solutions Joshua R. Davis PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Lecturer in Mathematics, Statistics, and Computer Science, Carleton College Alyson Doles BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Research Mathematician, US Army Corps of Engineers Skip Garibaldi PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Director, IDA Center for Communications Research

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Amanda Hanford PhD Acoustics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Assistant Research Professor in Acoustics, The Pennsylvania State University Marylesa Howard PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 Senior Scientist, Nevada National Security Site Aaron Luttman PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Principal Scientist, Nevada National Security Site Chad Magers MS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Scientist, Naval Surface Warfare Center Carol Meyers PhD Operations Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 Mathematician and Project Manager, Lawrence Livermore National Laboratory Erika Meza MPH Environmental Health Sciences . . . . . . . . . . . . . . . . . . . . . . . . . 127 Project Associate, The RAND Corporation Walter Morales MS Petroleum Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 Technologist, Chevron Corporation Grace Nabholz BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Research Mathematician, US Army Corps of Engineers Aisha N´ ajera Chesler PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . 147 Associate Mathematician, RAND Corporation Karoline Pershell PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 Lead Technical Researcher, Zenti, Inc. Emilie Purvine PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Data Scientist, Pacific Northwest National Laboratory Mary Lynn Reed PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 Chief, Mathematics Research Group, National Security Agency Bonita Saunders PhD Computational and Applied Mathematics . . . . . . . . . . 199 Mathematician, National Institute of Standards and Technology Andrew Stein PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215 Associate Director of Pharmacometrics, Novartis Andrea Walker MS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 Research and Development Manager, Sandia National Laboratories Chris Wiggins PhD Theoretical Physics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 Associate Professor, Columbia University; Chief Data Scientist, The NY Times Bryan Williams PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 Scientist, Space and Naval Warfare System Center Atlantic, US Navy

Sales and Marketing Lisa Byrne MS Mathematics and Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Data Scientist, WeddingWire Erick Deras BA Mathematics and Computer Science . . . . . . . . . . . . . . . . . . . . . . . 49 Lead Software Development Engineer, The Rubicon Project Samantha Drost BS Mathematics, BA Economics . . . . . . . . . . . . . . . . . . . . . . . . . 55 Senior Analyst, Business Intelligence and Analytics, Target Corporation Jaquelyn Fernandez Rieke BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Founder, Nutty Steph’s; Land Steward, Onion River Campground Erin Jones BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Go-To-Market and Sales Strategy Manager, RSA, Dell Technologies

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Stacey Faulkenberg Larsen PhD Mathematical Statistics . . . . . . . . . . . . . . . . 111 Lead Analyst, Business Intelligence and Analytics, Target Corporation Carissa Mendoza BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Senior Inside Sales Representative, Trace3 Jacqueline Nolis PhD Industrial Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Director of Analytics, Marketing and Sales Strategy Firm Ali Shappy MBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 Inventory Analyst, The Vermont Country Store

Sports Ben Baumer PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Assistant Professor, Smith College; Statistical Analyst, NY Mets Tim Chartier PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Professor, Mathematics and Computer Science, Davidson College Michael Dairyko PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Senior Manager – Data Scientist, Milwaukee Brewers Dean Oliver PhD Environmental Science and Engineering . . . . . . . . . . . . . . . . .157 Vice President of Data Science, TruMedia Networks Danielle Shepherd BA Mathematics and Physics . . . . . . . . . . . . . . . . . . . . . . . . . 211 Simulation Engineer, Chip Ganassi Racing

Statistics and Biostatistics Charlotte Abrams MPH Biostatistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Graduate Student, Columbia University Ben Baumer PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Assistant Professor, Smith College; Statistical Analyst, NY Mets Robert M. Bell PhD Mathematical Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Statistician (retired), RAND, AT&T, and Google, Inc. Lizette Ortega Dickey MS Biostatistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 Biostatistician, Contract Research Organization Stephanie Fitchett PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Statistician and Data Scientist, Transamerica Life Insurance Company Rachel Insoft BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Senior Analyst, Quantitative Economics and Statistics Group, Ernst & Young Liz Uribe MS Biostatistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 Biostatistician, University of Iowa

Writing and the Arts Dana Mackenzie PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Freelance Writer Alex McAdams PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Senior Software Engineer, Walt Disney Animation Studios

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Elizabeth Morgan MFA Theater Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Freelance Producer Gregory Rae BS Computer Science and Mathematics . . . . . . . . . . . . . . . . . . . . . 181 Producer and General Manager, Martian Entertainment Julie Shapiro BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Enterprise Editor, NBC News Digital

Contents by highest degree earned Bachelor’s Degree Brian T. Bares BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Founder and Chief Investment Officer, Bares Capital Management, Inc. Paige Bartholomew BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Consultant, Bain & Company Mimi Cukier BA Mathematics and Philosophy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Mathematics Teacher, The Park School of Baltimore Kathleen Daly BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Staff Engineer, Booz Allen Hamilton Erick Deras BA Mathematics and Computer Science . . . . . . . . . . . . . . . . . . . . . . . 49 Lead Software Development Engineer, The Rubicon Project Alyson Doles BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Research Mathematician, US Army Corps of Engineers Samantha Drost BS Mathematics, BA Economics . . . . . . . . . . . . . . . . . . . . . . . . . 55 Senior Analyst, Business Intelligence and Analytics, Target Corporation Jaquelyn Fernandez Rieke BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Founder, Nutty Steph’s; Land Steward, Onion River Campground Harold Hausman BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Owner and Senior Software Engineer, TechAscent Ebony Hitch BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .87 Mathematics Teacher, Wicomico High School Kelly Hobson BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 Software Tester, Internet of Things Solution, SAS Institute Rachel Insoft BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Senior Analyst, Quantitative Economics and Statistics Group, Ernst & Young Maribeth Johnson BA Mathematics and Neuroscience . . . . . . . . . . . . . . . . . . . . .99 Boost Consultant, Epic Systems Corporation Marina Johnson BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Analyst, Morgan Stanley Erin Jones BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Go-To-Market and Sales Strategy Manager, RSA, Dell Technologies Barbara Jordan BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Assistant Vice President, Credit Risk Management, GM Financial Carissa Mendoza BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Senior Inside Sales Representative, Trace3 Christopher Minck BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Fixed Income Trader, BlackRock 277

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Grace Nabholz BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Research Mathematician, US Army Corps of Engineers Gregory Rae BS Computer Science and Mathematics . . . . . . . . . . . . . . . . . . . . . 181 Producer and General Manager, Martian Entertainment Rachel Ramirez BA Mathematics with Actuarial Science Concentration . . . 183 Actuarial Analyst, National Life Group Adam Rich BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189 Actuary, Head of Specialty Lines Analytics, Beazley Group PLC Christina Roberts BA Mathematics and Spanish . . . . . . . . . . . . . . . . . . . . . . . . . 191 Assistant VP, Senior Catastrophe Modeling Analyst, Validus Reinsurance Shannon Rogers BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Curriculum Developer, Art of Problem Solving Kayli Schafer BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201 Enterprise Strategy Manager, OneAmerica Julie Shapiro BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Enterprise Editor, NBC News Digital Danielle Shepherd BA Mathematics and Physics . . . . . . . . . . . . . . . . . . . . . . . . . 211 Simulation Engineer, Chip Ganassi Racing Benjamin P. Simmons BA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213 Vice President, Risk Solutions, Gravie Courtney Stephens BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 CEO, QED Energy Associates Robert Troy BS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 Pilot, US Air Force

Master’s Degree Charlotte Abrams MPH Biostatistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Graduate Student, Columbia University Noelle Balandi MS Financial Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Finance Specialist, Multnomah County, Oregon Stacy Beaudoin MST Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Math Teacher, St. Paul’s School Ebonii Bell MA Computational and Applied Mathematics . . . . . . . . . . . . . . . . . . 15 Senior Supply Chain Analyst, Abbott Nicole Bertram MS Cellular and Molecular Biology . . . . . . . . . . . . . . . . . . . . . . . . 21 Software Developer, Epic Systems Corporation Kate Brady MA Urban and Environmental Planning . . . . . . . . . . . . . . . . . . . . . . . 25 Senior Bicycle Planner, City of Colorado Springs Sarah Brown MA Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Senior Scientist, NATO Communications and Information Agency Lisa Byrne MS Mathematics and Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Data Scientist, WeddingWire Lizette Ortega Dickey MS Biostatistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 Biostatistician, Contract Research Organization Kathie Flood MA Journalism and Mass Communications . . . . . . . . . . . . . . . . . . 69 CEO, Cascade Game Foundry SPC

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Tamara Fuenzalida MS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Instructor of Mathematics, Tarrant County College Northeast Angela Gallant MS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Mathematics Instructor, Inver Hills College Jennika Gold Thomas MS Computational Finance, MS Mathematics . . . . . . 79 Director of Strategy, Fixed Income Analytics, FactSet CJ Jaynes MS Mathematics, MBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Rear Admiral (ret), US Navy; Executive Technical Advisor, Raytheon Company Chad Magers MS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Scientist, Naval Surface Warfare Center Erika Meza MPH Environmental Health Sciences . . . . . . . . . . . . . . . . . . . . . . . . . 127 Project Associate, The RAND Corporation David Moore MS Environmental Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Environmental Products Analyst, Element Markets Walter Morales MS Petroleum Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137 Technologist, Chevron Corporation Janeth Moran-Cervantes MS Computer Science . . . . . . . . . . . . . . . . . . . . . . . . . 139 Software Development Engineer, Amazon Elizabeth Morgan MFA Theater Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Freelance Producer Christine Papai MS Mathematics, MDP International Development . . . . . . 161 Deputy Country Director, Innovations for Poverty Action Ghana Cara D. Petonic MBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .167 Director, Corporate Strategy, Comcast Corporation Jacqueline Pfadt MBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Technical Lead, Savantage Solution Kimberly Plesnicar MS Actuarial Science . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Actuarial Analyst II, Zurich North America Ali Shappy MBA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207 Inventory Analyst, The Vermont Country Store Alec Torigian Master of Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .227 Associate Director, Alliance for Catholic Education Teaching Fellows Jane Turnbull MS Applied Probability and Statistics . . . . . . . . . . . . . . . . . . . . . . 231 Assistant Vice President, Equifax Jasmin Uribe MS Applied Mathematics, MS Computer Science . . . . . . . . . . . 233 Research and Development Computer Scientist, Sandia National Laboratories Liz Uribe MS Biostatistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 Biostatistician, University of Iowa Kim Van Duzer MS Elementary Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 Teacher, Co-Founder of NYC Math Lab, NYC Department of Education Andrea Walker MS Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239 Research and Development Manager, Sandia National Laboratories Beatrice White MA Mathematics Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243 Math Teacher, Clinton Hill Middle School Donald C. Williams MA Computational and Applied Mathematics . . . . . . . 249 CEO, Director of Trading and Asset Management, Sion Capital, LLC

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PhD, MD, or JD Xiaoling (Ling Ling) Lim Ang PhD Economics . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Associate Director, NERA Economic Consulting Ben Baumer PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Assistant Professor, Smith College; Statistical Analyst, NY Mets Robert M. Bell PhD Mathematical Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Statistician (retired), RAND, AT&T, and Google, Inc. Nicholas Bennett PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Research Scientist, Schlumberger Toni Bluher PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 Subject Matter Expert in Cryptography, National Security Agency Marina Brockway PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Chief Technology Officer and Founder, VivaQuant Jenna Carpenter PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Founding Dean and Professor, Campbell University Tim Chartier PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Professor, Mathematics and Computer Science, Davidson College Bill Correll, Jr. PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Research Scientist, Radiant Solutions Carla Cotwright-Williams PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Computer Scientist, Hardy-Apfel IT Fellow, US Social Security Administration Michael Dairyko PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Senior Manager – Data Scientist, Milwaukee Brewers Joshua R. Davis PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Lecturer in Mathematics, Statistics, and Computer Science, Carleton College Kate Dyson Juris Doctor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Partner, White & Case LLP Berton Earnshaw PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Director, Data Science Research, Recursion Pharmaceuticals Chandra Erdman PhD Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 Senior Solutions Consultant, Google, Inc. Katie Evans PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Professor of Mathematics and Statistics, Louisiana Tech University Stephanie Fitchett PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Statistician and Data Scientist, Transamerica Life Insurance Company Skip Garibaldi PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Director, IDA Center for Communications Research Sommer Gentry PhD Electrical Engineering and Computer Science . . . . . . . . 77 Mathematics Professor, US Naval Academy Amanda (Quiring) Gonzales PhD Business Administration (Accounting) . 81 Assistant Professor of Accounting, University of Nebraska Lincoln Amanda Hanford PhD Acoustics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Assistant Research Professor in Acoustics, The Pennsylvania State University Marylesa Howard PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 Senior Scientist, Nevada National Security Site Eleisha Jackson PhD Ecology, Evolution, and Behavior . . . . . . . . . . . . . . . . . . . . 95 Data Scientist, Livongo

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Harlan Kadish PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Field Software Engineer, Tamr Inc. David Keyes PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Senior Program Manager, IXL Learning Stacey Faulkenberg Larsen PhD Mathematical Statistics . . . . . . . . . . . . . . . . 111 Lead Analyst, Business Intelligence and Analytics, Target Corporation Dan Loeb PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Quantitative Research Analyst, Susquehanna International Group Aaron Luttman PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Principal Scientist, Nevada National Security Site Dana Mackenzie PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Freelance Writer Alex McAdams PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Senior Software Engineer, Walt Disney Animation Studios Carol Meyers PhD Operations Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 Mathematician and Project Manager, Lawrence Livermore National Laboratory George Mohler PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Associate Professor, Indiana University-Purdue University Indianapolis Tanya Moore PhD Biostatistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 VP, Mission Advancement, Goodwill of San Francisco, San Mateo, and Marin Carol Muehrcke PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 Independent Cyber Security Consultant Aisha N´ ajera Chesler PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . 147 Associate Mathematician, RAND Corporation Andy Niedermaier PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 Trader, Jane Street Capital Jacqueline Nolis PhD Industrial Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 Director of Analytics, Marketing and Sales Strategy Firm Kyle Novak PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Deputy Chief Analyst, US Air Force (retired) Dean Oliver PhD Environmental Science and Engineering . . . . . . . . . . . . . . . . .157 Vice President of Data Science, TruMedia Networks Laurel Paget-Seekins PhD Civil Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 Director of Strategic Initiatives, Massachusetts Bay Transportation Authority Yolanda Parker PhD Mathematics Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 Mathematics Professor, Tarrant County College Karoline Pershell PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 Lead Technical Researcher, Zenti, Inc. Ashley Pitlyk PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 171 Senior Data Scientist, Care Otter Amanda Plunkett PhD Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .175 Analytic Team Lead, Department of Defense Elizabeth Pontius MD Medicine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 Attending Physician, MedStar Washington Hospital Center Emilie Purvine PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Data Scientist, Pacific Northwest National Laboratory Blake Rector PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185 Director of Analytics, Powin Energy

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Mary Lynn Reed PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 Chief, Mathematics Research Group, National Security Agency Lucas Sabalka PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 Computer Vision Specialist, Ocuvera, LLC Jeffrey Saltzman PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Proprietor, Cottonwood Applied Mathematics Bonita Saunders PhD Computational and Applied Mathematics . . . . . . . . . . 199 Mathematician, National Institute of Standards and Technology Jeanette Shakalli PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 Exec Asst, National Secretariat of Science, Technology & Innovation of Panama Richard Sharp PhD Applied and Computational Mathematics . . . . . . . . . . . . . 209 Data Scientist, Starbucks Andrew Stein PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 215 Associate Director of Pharmacometrics, Novartis Jean Steiner PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217 Senior Director of Data and Insights, Skillshare Sumanth Swaminathan PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . 221 Chief Data Scientist, Revon Systems Inc Rebecca Swanson PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223 Teaching Professor, Colorado School of Mines Shree Taylor PhD Applied Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 President and CEO, Delta Decisions of DC, LLC Clemmie B. Whatley PhD Educational Studies . . . . . . . . . . . . . . . . . . . . . . . . . . 241 Associate Professor, Mercer University; President, Educational Dynamix Chris Wiggins PhD Theoretical Physics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 Associate Professor, Columbia University; Chief Data Scientist, The NY Times Bryan Williams PhD Mathematics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 Scientist, Space and Naval Warfare System Center Atlantic, US Navy Joyce Yen PhD Industrial and Operations Engineering . . . . . . . . . . . . . . . . . . . . 251 Director, ADVANCE Program, University of Washington

AMS / MAA

CLASSROOM RESOURCE MATERIALS

What can you do with a degree in math? This book addresses this question with 125 career profiles written by people with degrees and backgrounds in mathematics. With job titles ranging from sports analyst to science writer to inventory specialist to CEO, the volume provides ample evidence that one really can do nearly anything with a degree in mathematics. These professionals share how their mathematical education shaped their career choices and how mathematics, or the skills acquired in a mathematics education, is used in their daily work. The degrees earned by the authors profiled here are a good mix of bachelors, masters, and PhDs. With 114 completely new profiles since the third edition, the careers featured within accurately reflect current trends in the job market. College mathematics faculty, high school teachers, and career counselors will all find this a useful resource. Career centers, mathematics departments, and student lounges should have a copy available for student browsing. In addition to the career profiles, the volume contains essays from career counseling professionals on the topics of job-searching, interviewing, and applying to graduate school.

For additional information and updates on this book, visit www.ams.org/bookpages/clrm-64

CLRM/64