Quico Spaen is a senior applied science leader with a decade of experience building large-scale optimization and machine learning systems to plan Amazon’s Middle Mile truckload and rail network. He leads teams that translate operations research and forecasting models into production-grade decision tools solving vehicle routing, equipment rebalancing, and demand prediction at continental scale. Trained as a Ph.D. in Operations Research with additional masters in ML and IEOR from UC Berkeley, he blends rigorous academic methods with pragmatic engineering to deliver measurable network efficiencies. Based in Sunnyvale, he has progressed through individual contributor and management roles at Amazon, pairing hands-on model development with cross-functional program leadership. Notably, his work focuses on hard combinatorial problems where scalable approximation and forecasting meet real-world logistics constraints.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Operations Research & Industrial Engineering, Doctor of Philosophy (Ph.D.) Operations Research & Industrial Engineering at University of California, Berkeley
Bachelor's Degree Liberal Arts and Sciences, Bachelor's Degree Liberal Arts and Sciences at Amsterdam University College
Pre-master Econometrics & Operations Research, Pre-master Econometrics & Operations Research at Erasmus University Rotterdam
Contributions:41 commits, 3 PRs, 14 pushes in 2 years 7 months
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Quico Spaen - Sr. Applied Science Manager at Amazon