Senior Data Scientist at Microsoft
Economist and data scientist with 14+ years of experience studying AI's impact on labor markets, productivity, and economic transformation. At Microsoft, I design and execute large-scale randomized controlled trials measuring LLM effects on knowledge work, generating rigorous causal estimates of how tools like Copilot change real productivity in enterprise settings.
I co-author Microsoft's Work Trend Index and New Future of Work reports, and have published research proposing AI as a macroeconomic factor of production and modeling how AI compresses coordination costs inside organizations. Eight years at the Bureau of Labor Statistics grounded this work in rigorous federal statistical methodology, improving estimation models for the Occupational Employment Statistics program and studying the causal effects of survey design on data collection.
I build open-source tools for labor market analysis: cmapr for career mobility research, onet2r for O*NET data, huggingfaceR for Hugging Face models in R, and foundryR for Azure AI Foundry. When I'm not working on that, I'm usually thinking about where economic intuition breaks down in an AI-augmented world, or playing jazz guitar.