Summary
Amanda Bower is a machine learning researcher and data scientist with a PhD in Applied Mathematics and nine years of experience building responsible, production-scale recommender systems. She has a strong theoretical foundation paired with hands-on experimentation at companies like Twitter and Netflix, where she shipped a recommendation fix that reduced inequality by 1.3% while improving quality by 2.28%. Her work focuses on algorithmic fairness, transparency, and accountability, including metrics and tooling now used internally to evaluate bias across ranking and moderation models. Amanda also mentors students and publishes first-author research on responsible recommendation, blending rigorous math with pragmatic solutions for real-world harms. Based in Ann Arbor, she maintains an academic-to-industry bridge that makes her equally comfortable proving theorems and running A/B tests.
8 years of coding experience
2 years of employment as a software developer
Master's degree, Applied Mathematics, Master's degree, Applied Mathematics at University of Michigan - Rackham Graduate School
Bachelor's degree, Mathematics, Bachelor's degree, Mathematics at University of Michigan-Dearborn