I’m a Senior Economist at Amazon, on the Demand Forecasting team. I work at the intersection of time-series econometrics and machine learning to produce forecasting models for a variety of demand series across Amazon. My research on applied time-series forecasting has been published by the National Bureau of Economic Research (NBER) and the International Conference on Machine Learning (ICML).

I hold a PhD in financial economics from Harvard University, where I was advised by Jeremy Stein. My research focused on applying tools from state-space modeling and machine learning to a variety of subject areas in financial economics, ranging from bond pricing to seasonal adjustment. Before grad school, I was a Business Analyst at McKinsey & Company, where I helped companies and governments solve strategic and operational problems. Before that, I was an undergrad at Columbia University where I worked with Serena Ng on analyzing macro trends in “big” retail purchasing data, wrote a senior thesis on the behavioral finance of Bitcoin advised by José Scheinkman, and did some internships in finance/tech.

I’m always interested in talking to people with similar research interests—if you’d like to chat, feel free to drop me an email at firstnamelastname at gmail dot com.