I am an Applied Scientist/Economist at Uber, where I build and productionize experiment design and measurement tools for Search Engine Optimization (SEO) and Ads Experiments. My work focusses primarily on geo-level and switchback experiments. I also work on spend allocation tools used by marketing partners to allocate budget across channels while maximizing target KPIs. 

Prior to Uber, I was a Data Scientist (Engineering) at Google, where I worked on ads experimentation and measurement for Google marketing teams. I built machine-learning driven tools to help identify and target high-propensity users and drive spend efficiency. Additionally, I worked on debiasing methods for brand surveys administered through Google Opinion Rewards (GOR) platforms. 

I received my PhD in Economics from Yale in May, 2022. At Yale, my primary field of research was labor economics and I studied the role of information and behavioral norms in the functioning of labor markets. I maintain a working site of my published and in-progress research papers. 

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