I’m an economist who occasionally brings data science techniques to economic analysis. I graduated from Emory University in USA, with a B.A. in economics and later obtained my M.Sc. in economics from Universität Bonn in Germany, where my thesis specialized in the applications of machine learning to large and complex datasets for causal inference.
I’m passionate about leveraging frontier machine learning methods to study the impact of economic policy and to spur the clean energy transition in emerging economies. As an economics researcher at The Wharton School, I co-developed a data package for evaluating the impact of land protection policies in the EU. Before that, I was at the United Nations University - Institute of Environment & Human Security, where I developed a sophisticated ML model using advanced cluster analysis to understand the different how people think and feel about urban sustainability in Latin America.
After gaining research experience in US and Germany, I joined S&P Global Market Intelligence in Dubai, UAE, as an economic consultant. I am now focused on applied economics, including time series forecasting, cost-modeling, and statistical analysis. Exposure to S&P Global’s unparalleled depth of data gives me an exciting opportunity to use my data science and big data skillset to develop customized solutions for a range of clients and industries.
On this website, you can find details about my past projects, research publications, and experiences in using data in new and innovative ways.
All views and opinions expressed on this website are solely my own and do not necessarily reflect the views, opinions, or official policies of any organization, employer, or entity I am associated with, unless explicitly stated.