Director of Analytics and Data Storytelling at Microsoft
I am an economist and data storyteller with more than fourteen years of experience, first as a federal economist and now at Microsoft, where I study how AI is reshaping work and productivity. Across both chapters the throughline has been the same: do the empirical work carefully, then make the findings clear enough to be useful to the people who have to act on them.
At Microsoft I run empirical research on how AI changes knowledge work. I design field experiments and randomized controlled trials, including the published study behind Scaffolding Human-AI Collaboration, and pair them with large-scale behavioral and survey data so the conclusions rest on credible causal evidence rather than anecdote. I co-author Microsoft's Work Trend Index and New Future of Work reports, and I write about where the economics is heading: Evolving the Productivity Equation asks whether AI should count as a new factor of production, and AI as Coordination-Compressing Capital models how AI reorganizes the firm from the inside. Before Microsoft, eight years as a federal economist at the U.S. Department of Labor, moving between the Bureau of Labor Statistics and the unemployment insurance program, grounded this work in rigorous federal statistical methodology, including improvements to the estimation models behind the Occupational Employment Statistics program.
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.