Igor Geyn, PhD Applied Data Scientist SF Bay Area

igorgeyn@gmail.com · LinkedIn · Resume PDF · Academic CV

Applied data scientist and researcher with a publication record and 10 years of experience. I specialize in clean delivery of complicated analysis, workflow automation, applied machine learning, and causal inference. Experienced in navigating complex policy and regulatory environments across large enterprises, research organizations, and lean startups.

Experience

Held during PhD program

Economist The Burning Glass Institute

Conduct research on workforce trends as part of a team of economists. Leverage public and proprietary data to answer policy and business questions (e.g., designing workforce development programs) for clients. Provide subject matter expertise on research design, statistics, causal inference, and ML. Build user-facing dashboards and other visual outputs.

Data Scientist PG&E

Automated analysis across dozens of enterprise risks using Python, SQL, and AWS, reducing preparation time and shortening regulatory filings by weeks. Built interactive tools for risk scenarios, program effectiveness, causal analysis, and senior-stakeholder communication; performed PG&E's first causal analysis of wildfire prevention programs. Promoted from Data Science Intern.

Survey Science Intern Veo

Combined causal inference techniques (geo discontinuity, SynthDiD) with re-weighted customer survey data (MrP) to plan product expansion (R + Python). Analyzed dataset with thousands of user survey responses and millions of rides generated by in-app customer behavior. Executed several natural experiments to identify previously unseen business opportunities.

Research Fellow D.C. Policy Center

Co-authored 4 policy reports on D.C. health workforce access and disparities. Combined ACS data, FOIA records, and original geocoding to produce first publicly available analysis of D.C.'s health workforce.

Graduate Student Researcher UCLA Center for Health Policy Research

Evaluated California health program effectiveness using difference-in-differences methodology.

Sr. Data Analyst Bloomberg Government

Wrote production code to enhance customer data. Conducted UX research using ML to improve contract detail prediction and linkages across millions of contracts. Improved web application experience for BGOV and Bloomberg Terminal products. Assisted company-wide cloud migration.

Sr. Research Analyst Atlantic Media

Led multi-analyst team executing a multi-million dollar flagship research product for Fortune 500 clients. Delivered market and marketing analyses using MaxDiff, conjoint, complex survey weighting, R, and Qualtrics across 100+ client engagements. Promoted from Research Analyst.

Research Analyst UCSF

Conducted quantitative and qualitative research for grant-funded projects on health workforce shortage, regional disparities, pilot program evaluation, and forecasting (primarily R). Co-authored 4 policy reports including statewide physician workforce analysis for the California Health Care Foundation. Coordinated large, state-funded evaluation programs and other projects.

Education

Ph.D. Political Science
UCLA · 2026
Statistics and Methodology Focus, GPA: 4.0
B.A. Economics and Political Science
UC San Diego · 2015
Departmental High Honors, Pi Sigma Alpha

Technical Skills

Languages Python (pandas, NumPy, scikit-learn, Polars, DuckDB) · R (tidyverse, fixest, did) · SQL
ML/Stats GLMs/regularization · XGBoost/LightGBM · Feature engineering & pipelines · CV · Calibration · Uplift/causal ML · SHAP
Causal A/B testing · DiD/RD/IV · Matching
Data/Cloud dbt/Dataform · Airflow/Composer · BigQuery/Vertex AI · Snowflake · Docker · PostgreSQL · Foundry
Bayes PyMC/Stan (MCMC)

Honors & Awards

Summer Research Grant
California Policy Lab · 2022
$10,000 award for promising graduate research (co-awarded with D. Firoozi)
Mentored Research Fund
UCLA · 2021
Support for independent research in political science
Star Award for Excellence
GovExec · 2019
Recognized for planning and execution of Leading Brands in Government