Summary
Manuel Molina is a data scientist with 11 years of professional experience who blends rigorous academic training (PhD and MS in Economics from the University of Maryland) with hands-on industry practice at Meta, where he progressed from a data science intern to a full-time role. He specializes in quantitative economics, econometrics, macroeconomics, and machine learning, applying these tools to problems in finance, education, and policy. Manuel has taught Money and Banking at the University of Maryland, signaling an ability to communicate complex ideas clearly to diverse audiences. Based in New York, he pairs a strong econometric research background with practical data engineering and analysis skills, and his international education (Universidad EAFIT and study abroad at Purdue) gives him a global perspective on economic problems.
11 years of coding experience
Doctor of Philosophy - PhD, Economics, Doctor of Philosophy - PhD, Economics at University of Maryland
Bachelor's degree, Economics, Bachelor's degree, Economics at Universidad EAFIT
Study Abroad, Study Abroad at Purdue University
Italian, Spanish, English