Ryan Grose is a New York City–based data engineer with nine years of experience building end-to-end cloud data solutions that move ideas from collection to AI-backed prediction. He designs lean, serverless pipelines and inference systems—frequently using Python and AWS—for production-grade multimedia and computer vision workloads, and has crossed into front-end, product, and hiring responsibilities when projects required it. His background spans hedge-fund scale data engineering at Point72, startup experimentation at Curie, and client-facing software work while traveling, showing both rigor and adaptability. Practicality and simplicity guide his approach: he favors functional, well-crafted code and command-line tools that make complex systems easy to operate.
9 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Computer Science with Data Science Option, Bachelor's degree, Computer Science with Data Science Option at University of Washington
Computer Science, Computer Science at KTH Royal Institute of Technology
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