About

I’m a data scientist at Grow Progress; we test ads and do survey research, helping Democrats and progressive organizations win elections. Before this, I was a data science manager at 605, where I worked on problems of causal inference, forecasting, and heterogeneous treatment effects modeling.

Some recurring themes of my work are modern methods for survey weighting, efficient estimation of causal effects, and scalable Bayesian inference.

Before grad school, I was a field and data staffer up and down the ballot in Minnesota. When not thinking about politics, I can most often be found running, reading, or playing ssbm.