Summary
Lenny Fan is a seasoned machine learning engineer with 10 years of experience building pricing and recommendation systems, currently contributing at Meta after leading pricing initiatives at Roadie. He has repeatedly delivered production-grade dynamic pricing models—one implementation saved an estimated $5M annually—and built end-to-end pricing infrastructure that serves multiple business applications. Lenny’s background blends applied math and engineering (M.S. in Applied Mathematics & Statistics, MEng in Engineering Management) with hands-on skills in Python, C#, SQL, Gurobi and optimization methods like mixed-integer programming. He pairs data-driven modeling with business consulting, routinely translating client data into pricing strategy and margin improvements. A practical problem-solver, he once accelerated an optimization model by 120x through targeted variable filtering and Big-M improvements, showing expertise beyond standard ML pipelines.
9 years of coding experience
8 years of employment as a software developer
Bachelor of Engineering (BE), Civil Engineering, Bachelor of Engineering (BE), Civil Engineering at National Taiwan University
Johns Hopkins University
Chinese, English