Summary
Nathaniel Poor is a founder and computational social scientist with a PhD in communication studies from the University of Michigan and over a decade of experience turning messy online media and game data into clear, actionable insights. He combines quantitative and qualitative methods—case studies, web scraping with Python and regex, R visualizations with ggplot and Gephi, and survey design—to answer questions at the intersection of technology and society. Comfortable both in academic and applied settings, he has held roles from lecturer and research associate to data fellow and political data volunteer, and now leads the Underwood Institute. His background uniquely blends humanities, mathematics, and early computing (learned Pascal on a VAX) with modern data tooling, and he enjoys digging into syntax and tooling details—whether tweaking SPSS scripts in the past or crafting reproducible R and Python workflows today. Based in Louisville, KY, he is as comfortable managing projects and presenting findings as he is elbow-deep in messy datasets.
12 years of coding experience
1 year of employment as a software developer
General Assembly
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at University of Michigan
BB&N
BS, BS at Hobart and William Smith Colleges
English, Spanish