Robert Rupf is a Senior Data Scientist with 15 years of experience building data models, automation pipelines, and analytics that turn messy measurement streams into actionable insights. Based in Toronto, he blends advanced statistical methods (GLMs, clustering) and deep learning with practical engineering—SQL/NoSQL schemas, RESTful APIs, Flask apps, and cloud-native scaling on Azure—to improve data collection, reporting, and visualization. He has a strong track record in high-performance sport, developing novel IMU-based algorithms and talent-identification metrics that contributed to Olympic and Paralympic athlete development. At Manulife and previously at Trizar Performance and national sport programs, he has translated research-grade methods from his PhD-level kinesiology background into production-ready tools. Colleagues rely on him to bridge domain science and software delivery, often surfacing non-obvious signals from athlete kinematics and longitudinal testing data.
15 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Kinesiology and Exercise Science, Doctor of Philosophy - PhD, Kinesiology and Exercise Science at University of Toronto
Contributions:8 pushes, 1 branch in 2 years 6 months
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