I’m a data scientist interested in learning about behavior via experimentation, causal inference, surveys, and online data. I am a Senior Data Scientist at Fable developing metrics, analyzing experiments, and providing strategic recommendations based on user behavior. Previously, I have been in PM, data scientist, and tech lead roles doing Experimentation at Pinterest.
As a statistician, I believe that we should always question assumptions and look at the big picture, not just the p-value. I enjoy uncovering opportunities to make other peoples’ work easier and more trustworthy, and designing tools to bridge that gap.
I received my PhD in Statistics from UC Berkeley in 2019. I was a Fellow at the Berkeley Institute for Data Science and my advisor was Philip Stark. My PhD work lies at the intersection of Statistics and Social Good. I’ve analyzed data to uncover gender bias in teaching evaluations, evaluate the impact of nutritional policies, and uncover anomalous results in U.S. elections.
Outside of statistics, I am passionate about food and fitness.