Tanner Fiez is an Applied Scientist II based in Seattle with nine years of experience bridging academic research and production machine learning at Amazon Prime. He specializes in sequential decision-making, multi-armed bandits, and learning dynamics—skills honed through a PhD and years as a graduate researcher and applied scientist intern working on auto-targeting and recommendation systems. At Amazon he focuses on simulation and experimentation for PubTech and Prime ML, translating theoretical bandit solutions into scalable production experiments. His background in electrical and computer engineering (magna cum laude) and early work on signal sensing and large-scale data parsing give him a strong foundation in both hardware-adjacent measurement systems and robust ML pipelines. Colleagues describe him as a scientist who favors principled methods but consistently delivers practical, production-ready solutions.
9 years of coding experience
7 years of employment as a software developer
Master's degree, Electrical and Computer Engineering, 3.86, Master's degree, Electrical and Computer Engineering, 3.86 at University of Washington
Bachelor's degree, Electrical and Computer Engineering, 3.96, Bachelor's degree, Electrical and Computer Engineering, 3.96 at Oregon State University
Contributions:14 commits, 12 pushes, 2 branches in 1 year 1 month
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