Exploring Appalachia through Data Science A year after graduating, Tim Pierce ’20 uses data science to map job skills in Appalachian labor markets.

Tim Pierce ’20

When Tim Pierce ’20 began leading a summer research team for the interuniversity consortium Data Science for the Public Good, he knew he’d have to learn quickly. Pierce, now entering his second year of a master’s degree in agricultural and applied economics at Virginia Tech, had one week packed full of onboarding before taking responsibility for four undergraduate interns on two projects.

“I felt very grateful for how Washington and Lee prepared me to learn very quickly,” he said, “and then take that learning and translate it to teaching. There is always uncertainty about the ability to learn new, challenging material, but I was really happy with the pace that I was able to learn new skills and apply them to the work.”

Over 10 weeks, Pierce and his team took anonymized data from the American Community Survey — similar to the census but smaller in scope and conducted annually — and built skill maps of Appalachia, highlighting the strengths and weaknesses of local labor markets in various job skills, from reading comprehension to technology design.

“We were able to do all kinds of really fun and occasionally frustrating data organization and linking,” he said. “It allows us to better understand the heterogeneity of skills throughout the Appalachian region.”

Ultimately, their techniques could be expanded to create similar maps for the entire country, helping policymakers understand the challenges and opportunities in rural labor markets at a deeper and more granular level.

Pierce was a senior economics major when W&L instituted its Data Science minor, and he was too close to graduation to declare the minor himself. But his master’s program felt well suited to the interest in public policy he discovered taking Development Economics and Advanced Topics in Micro and Macroeconomics, and he found himself well prepared for the work.

“This project was not terribly unlike my econometrics term paper,” he said. “Using the data science approach where you identify a problem, you identify the appropriate data source for that problem, you examine the data and then you display the data — that’s a lot of what we did in econometrics at W&L and a lot of what we did here.”

Between his master’s experience and his foundation from W&L, Pierce sees plenty of opportunities available for him, from working in a government role or pursuing a Ph.D. in economics to joining a consulting firm and doing computational modeling.

“These fields are all increasingly interdisciplinary,” he said, explaining that his colleagues at Data Science for the Public Good majored in sociology, economics, computer science and more. “Policy is going to be driven by data science, which is ultimately informed by theory, and it’s the study of how people behave and interact, which is very sociological. Everyone is using data science and statistics and everyone’s research is motivated by the theory.”

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