Embedded Files
Download my full CV here:
I have completed two economist internships at Amazon, applying causal inference and machine learning methods to large-scale field experiment and forecasting problems.
WW Prime Science Economist Intern
WW Prime Science Economist Intern
Amazon, May 2025 – August 2025
As an economist intern on the Worldwide Prime Science team, I estimated the causal effect of delivery speed on customer subscription behavior and spending using instrumented difference-in-differences models applied to field experiment data. I then used these experimental results to validate a high-dimensional fixed-effects observational model, identifying the features that most improved causal estimation at scale.
SCOT Forecasting Economist Intern
SCOT Forecasting Economist Intern
Amazon, May 2024 – August 2024
Working with Amazon's Supply Chain Optimization Technologies (SCOT) organization, I trained Wasserstein Generative Adversarial Networks (WGANs) in PyTorch to generate synthetic counterfactual data for validating causal models. This work identified and characterized the specific aspects of machine-learning-based causal models that contributed to estimation inaccuracies, informing improvements to the team's forecasting approach.
Page updated
Google Sites
Report abuse