Patrick Gerbes is a data scientist with a decade of experience turning ill-defined, high-impact problems into practical, production-ready solutions by blending mathematics, research, and software engineering. He has led data teams at companies like SuperRare Labs and Storj, applying expertise in unsupervised and supervised learning, operations research, econometrics, and computer vision to real-world systems. Comfortable across Scala, R, Haskell, Spark and cloud tooling, he bridges experimental modeling with scalable data pipelines and deployment. Patrick’s background in economics and math fuels a probabilistic, optimization-first approach to forecasting and assignment problems, and he thrives on problems that demand creativity as much as rigor. Based in Atlanta, he pairs hands-on implementation with a research mindset focused on technologies that can materially change industries.
10 years of coding experience
10 years of employment as a software developer
BA, Economics, Math, BA, Economics, Math at Boston University
Contributions:38 pushes, 4 branches in 1 year 3 months
apistorj-networkstorjrestrest-api
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