Yihao Wang is an applied analytics professional and Columbia MS candidate with four years of experience turning transportation data into operational impact. At Uber he built location-optimization and clustering solutions, visualized NYC trip patterns with Folium, and prototyped predictive models (Lasso, GBDT, XGBoost, LSTM) to forecast hourly demand across zip codes. He blends strong quantitative training from Columbia and Lehigh with practical Python engineering to deliver decision-focused analytics for routing, dynamic pricing, and dispatch optimization. Based in New York, he pairs a near-perfect graduate GPA with hands-on experience deploying spatial analytics and time-series models, and has a knack for making complex travel-uncertainty problems tractable.
4 years of coding experience
Master of Science - MS, Applied Analytics, 3.96, Master of Science - MS, Applied Analytics, 3.96 at Columbia University School of Professional Studies
Undergraduate, Business and Economics, 3.7, Undergraduate, Business and Economics, 3.7 at Lehigh University - College of Business and Economics
Contributions:5 releases, 87 commits, 8 PRs in 10 months
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