Igor Geyn
Data (+ Social) Scientist

Hello! My name is Igor. I live and work in the San Francisco (CA) Bay Area.

I'm a data scientist and social science researcher specializing in causal inference using large data sets, advanced econometric methods, complicated data pipelines (including non-traditional data sources), and machine learning. My PhD research focuses on answering local political economy questions such as "do partisan elections lead to biased election results?" (they haven't), "does going to college cause attendees to paricipate in politics?" (it does), and "can/do voters learn from local ballot measures and propositions?" (work in progress, early results suggest small/negligible effects under some specifications).

I am currently working as a part-time economist with The Burning Glass Institute, working with a team of researchers to answer questions about the future of work, the impact of AI on demand for skills, and other client-facing engagements. My projects focus on contributing methodological advances and driving empirical rigor. 

During academic year 2024-25, I used a leave of absence to build automated tools for risk analysis as well as perform causal analysis of wildfire mitigation programs at Pacific Gas & Electric Company (PG&E), one of the nation's largest invester owned utilities (IOUs) and a budget in the tens of billions of dollars. 

I got my taste for social science (and decided to pursue a PhD) after about half a decade getting my feet wet as a researcher at a health workforce institute in San Francisco and at several companies in Washington, D.C. focused on government technology, defense, and professional services. I have spent time as a freelance journalist, people manager, philanthropic organizer, assistant caterer, and many other roles.

I am actively seeking full-time employment (am "on the job market") with a primary goal of improving inference (both human and machine-based) at scale. 

Contact: igorgeyn at gmail dot com  |  LinkedIn: profile  |  CV: [link]