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Why James Martter Returned to School to Study Data Science
James Martter
Education
M.S. in Data Science 2027, University of Virginia
B.A. in Economics and Computer Science 2017, Harvard University
Hometown
Akron, Ohio
James Martter’s path to data science didn’t follow a straight line—and that’s exactly what makes it compelling. From studying economics and competing as a varsity athlete at Harvard, to rotating through leadership roles at Anheuser-Busch, and now working at a quantitative hedge fund, Martter has seen firsthand how data shapes decision-making across industries and at every level of an organization.
Now an M.S. in Data Science (MSDS) online student at the University of Virginia (UVA), Martter is intentionally deepening his technical foundation to complement years of real-world analytical experience. In this profile, he reflects on the moments that sparked his pivot into data science, what drew him to UVA’s MSDS program, and how he’s preparing to grow as both a practitioner and a leader in an increasingly data-driven world.
Q: Tell us about your path to data science.
I studied economics at Harvard, where I also played varsity football. I realized late how much I enjoyed technical courses (e.g., statistics, econometrics) and had just enough time to add a Computer Science secondary. That curriculum provided just enough data science exposure to be fascinated, without enough hands-on training to be a real practitioner.
After graduation, I joined Anheuser-Busch as part of their Global Management Trainee program, rotating through departments across the country — from sales ride-alongs in Los Angeles to shoveling Budweiser beechwood chips in the St. Louis brewery. It was a foundational experience that gave me visibility into virtually every corner of a major CPG firm. Across all those functions, the clearest throughline I detected was that data had become absolutely central in modern business decision-making. At the time, I was shocked to find data was just as critical in HR and Procurement as it was in Sales and Marketing.
I held many roles at Anheuser-Busch, bringing a strong analytical lean to each of them while learning SQL, Excel, and BI tooling. The last role I held was in general management at one of their craft breweries, which offered a glimpse into executive leadership. That was the most challenging and rewarding role of my career, and my biggest takeaway was that, at the end of the day, I was still most engaged when analyzing data and storytelling in pursuit of sound decision-making.
Since then, I've been executing a steady pivot into "proper" data science. Today, I work at Two Sigma Investments, a quantitative hedge fund where data science is deeply embedded in every aspect of the firm’s work.
Q: What do you hope to do with a M.S. in Data Science degree?
Right now, I’d describe myself as a self-taught data analyst and an aspiring data scientist. I often liken it to being a guitar player who can play well by ear but cannot read music or tell you much about music theory. With this M.S. in Data Science, I hope to solidify my foundational understanding before continuing to more advanced applications like Machine Learning.
After graduation, I hope to expand my contributions at Two Sigma, grow into leadership roles where I can mentor data scientists, and pursue personal data science projects that I’ve put on hold while filling in technical gaps.
Q: What has surprised you about the MSDS program so far?
The energy from professors, support staff, and classmates is palpable. I’ve been out of school for a while and wasn’t sure what to expect, but UVA has cultivated a learning environment that feels genuinely supportive, enthusiastic, and dynamic.
Q: What class do you look forward to taking?
There are so many exciting electives that I might have to petition for extras! Right now, courses like Bayesian Machine Learning, Business Analytics for Data Scientists, and How to Train Your LLM really stand out to me.
Q: What advice would you give to someone considering a master’s in data science?
Focus less on memorizing tools or syntax and more on understanding core concepts: statistics, probability, algorithmic thinking, and communication. In a world with LLM copilots, fluency in tools will become easier to acquire (or altogether unnecessary), and the ability to reason clearly and explain your work will only become more important.
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Q: What are some fun facts about yourself?
I was living in Manhattan when the COVID-19 pandemic hit, and escaped in a converted campervan with my now-wife. We’re just part-time van-lifers these days, but earlier this year we completed a years-long journey to visit all 51 U.S. National Parks in the Lower 48. We hope to eventually make it to all of them.
Learn more about the part-time, 100% online M.S. in Data Science at the University of Virginia. Request more information, connect with Admissions, or start your application today.
