I am a Senior Data Scientist at Netflix. In my professional work, I use Economics, Statistics, and Computer Science to build systems that inform high-stakes business decisions.
At Netflix, I use machine learning to engineer statistical tools that help us decide which titles to license, which scripts to make into shows, and which talent to sign. Prior to Netflix, I was an Economist at Amazon, where I leveraged their large customer data set to build causal econometric models that determine how Amazon Prime members are attributed and how investments are to be allocated across Amazon's various businesses like retail, video, music, and hardware devices. I hold a Ph.D. in Economics from Stanford University, where I spent 5 years conducting research in theoretical econometrics and machine learning.
On the side, I am also an Adjunct Professor of Economics at the University of Southern California. In Spring 2018, I will be teaching a graduate course on Machine Learning and Causal Inference. I also advise technology startups on how to create data-driven companies.