Consulting in causal inference, survey research, policy analysis, and labor-market analytics.
DiD, regression discontinuity, synthetic controls, and other approaches for estimating effects when experiments are not feasible.
Questionnaire design, fielding, analysis, visualization, and presentation for studies with public, consumer, or stakeholder audiences.
Clear public-facing analysis from messy administrative, survey, labor-market, and open-source datasets.
Work on AI exposure, skills demand, workforce trends, occupational change, and labor-market data products.
Research support for an award-winning investigative series on labor conditions in U.S. recycling facilities: OSHA/BLS analysis, Python scraping, and original writing.
Managed GovExec's flagship brand study: coordinated a 5,000+ response survey, built presentation assets, and delivered findings used for marketing and lead generation.
First publicly available analysis of D.C.'s health workforce, combining public data, FOIA records, and original geocoding.
Part-time economist on AI, future-of-work, and labor-market trends: NLP and causal-inference analyses of AI exposure across industries and countries, plus a public-facing app for state and local officials. BGI research →
Survey methodology and causal inference for a micromobility company, including approaches to estimate treatment effects from observational rider data when A/B testing was not possible.
Statistical consulting on racial disparities under the Racial Justice Act.
Analysis plan for natural experiments in a high-spillover setting.
"We trust Igor with one of our flagship ventures and would recommend him to anyone with data, visualization, and presentation needs." — Frank Salatto, SVP Brand & Strategy, GovExec
"He's found innovative ways to collect data we needed, shown ability to work with different types of datasets and provided thoughtful analysis." — Cole Rosengren, Senior Editor, Waste Dive