Jason Gellis is a data scientist and evolutionary biologist with 11 years of experience applying machine learning, computer vision, and large-scale data engineering to questions in human evolution, biogeography, and product analytics. He has led global teams to deliver production data pipelines and interactive analytic products using Python, React, cloud platforms, and generative AI methods, and previously developed open-source tools like PyLithics for archaeological lithic analysis. A PhD-trained researcher and award-winning scientist, he translates complex technical and biological findings into actionable insights for academic and commercial stakeholders. Jason’s work uniquely bridges fieldwork and fossil imaging with enterprise delivery—recovering and analyzing ancient material while steering client-facing data products at scale. Based in Bristol, he combines rigorous academic publishing and editorial experience with hands-on leadership in data science delivery.
11 years of coding experience
8 years of employment as a software developer
BA, Liberal Arts and Sciences, General Studies and Humanities, Dean's List, BA, Liberal Arts and Sciences, General Studies and Humanities, Dean's List at San Francisco State University
Doctor of Philosophy (Ph.D.), Biological Anthropology, Thesis: Root Problems in Human Variation, Doctor of Philosophy (Ph.D.), Biological Anthropology, Thesis: Root Problems in Human Variation at University of Cambridge
Master of Science (MSc), Palaeoanthropology, Thesis: Testing Spatial Hypotheses of Mandibular Shape and Form - Distinction, Master of Science (MSc), Palaeoanthropology, Thesis: Testing Spatial Hypotheses of Mandibular Shape and Form - Distinction at The University of Sheffield
Test de Connaissance du Français (TCF, or French Knowledge Test), French, History, Anthropology, Test de Connaissance du Français (TCF, or French Knowledge Test), French, History, Anthropology at Sorbonne University
Contributions:2 PRs, 4 pushes, 3 branches in 6 years 8 months
javapython
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