At the forefront of data science
A former UO grad student melds multiple disciplines to blaze trails in an emerging field.
Thomas Miller prides himself on being multilingual—in the languages of business and technology. As a graduate student pursuing an MBA at the University of Oregon years ago, he quickly realized that many of the disciplines he was interested in didn’t speak the same languages. “I was not satisfied…a lot of people in business didn’t understand economics that well,” he recalls.
So he decided to branch out, and earned a second M.S. in economics. He also pursued a PhD in psychology at the University of Minnesota and another Master’s in statistics, and launched his career working in a variety of technology and transportation companies. Along the way, he developed programming and a host of other IT skills.
And the strategy paid off. “Being multi-disciplinary—‘multilingual,’ if you will—is an advantage when it comes to getting things done and working in teams,” Miller says.
Today, he has blended these varied interests to become a leader in an emerging field. Miller teaches a variety of graduate courses in predictive analytics, a master’s program offered by Northwestern University.
Originally envisioned as a program with 150-200 students, the MS in Predictive Analytics has grown to be the largest graduate program at Northwestern, and the largest graduate program of its kind in the world.
Data analytics, or data science, as many have dubbed it, merges the disciplines of programming, econometrics, statistics, and even consumer behavior when used in marketing and other fields.
“We are living in a data-driven, data-intensive world. These data are of interest to organizations of all kinds, and the analysis of these data is the job of predictive analytics. It’s a high growth area.”
Miller sees data science continuing to expand, and believes that students with a firm grounding in economics can be very successful in this emerging field. “A lot of our students have economics degrees as undergraduates,” he says. “It’s a good signal that you’ll do well. Working with data, building models, testing those models…. these are key skills across many occupations.”
Miller continued: “While I was at UO, I first learned about discrete choice models, which have been very important to me in subsequent teaching and consulting.”
His advice to economics undergrads interested in data science? “Get a good background in statistics and econometrics,” he says. “But don’t restrict yourself to the languages and systems that are used in your economics courses. Look to the industry in general.”
Miller believes programming and IT experience is especially valuable to students who are looking to boost their resumes. “Which [programming] languages are being used today? Take a look at R and Python. Take on independent study projects that give you a chance to try things out using open source tools and systems. You do not need to major in computer science to do these things.”
His other advice: “It’s a good thing to have a learning attitude. As soon as you think you know enough, you start falling behind.”
Recent books by Thomas W. Miller
Miller, T. W. (2015). Web and Network Data Science: Modeling Techniques in Predictive Analytics. Upper Saddle River, N.J.: Pearson FT Press. [ISBN-13: 978-0-13-388644-3]
Miller, T. W. (in press). Marketing Data Science: Modeling Techniques in Predictive Analytics with Python and R. Upper Saddle River, N.J.: Pearson FT Press. [ISBN-13: 978-0-13-388655-9] We expect this to be available in May.