Summary
Kensen Tan is a data scientist based in the San Francisco Bay Area with 7 years of hands-on experience building end-to-end analytics and ML solutions and a total of 15 years of professional experience. He has applied data-driven product thinking across tech and insurance domains at Lyft, Facebook, Cover, Vroom, and Farmers Insurance, moving models from prototype to production. Kensen holds dual MS degrees in Computer Science and Analytics from Georgia Tech and a BA in Statistics from UC Berkeley, blending strong statistical foundations with scalable engineering. He’s comfortable across the full stack of data work—feature engineering, causal analysis, model deployment, and product metrics—and has mentored students as a graduate teaching assistant. Known for translating ambiguous business problems into measurable experiments, he thrives in fast-paced product teams where delivering impact quickly matters. Outside core roles he repeatedly intersects research-grade methods with production constraints, making sophisticated techniques pragmatic for stakeholders.
15 years of coding experience
5 years of employment as a software developer
Bachelor of Arts - BA, Statistics, Bachelor of Arts - BA, Statistics at University of California, Berkeley
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Georgia Institute of Technology
English, Chinese, Chinese