Daniel Dafoe is a data scientist with 11 years of hands-on experience building production-ready ML and data engineering solutions across computer vision, cloud systems, and backend development. He has moved models from research to product—developing photogrammetry and mobile CV pipelines, training Faster/Mask R-CNN detectors, and migrating workloads between local and distributed cloud environments. As a tutor and instructor he translates complex concepts into practical skills, leading bootcamp webinars, mock interviews, and curriculum scripts that help others ship work faster. He combines a BS in Statistics with recent AI study at Nebius Academy, and brings a practical, metric-driven mindset honed through research roles at universities and consulting projects for organizations like the World Bank. Based in California, he pairs curiosity-driven learning with collaborative engineering to tackle ambiguous problems end-to-end. An underrated strength is his background in personal training and client-facing coaching, which informs his clear communication and habit of turning data into actionable progress.
11 years of coding experience
6 years of employment as a software developer
California Polytechnic State University, San Luis Obispo
Artificial Intelligence, Artificial Intelligence at Nebius Academy
Contributions:105 commits, 43 pushes, 6 branches in 1 year 6 months
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