Alan Sabino is a Senior Data Scientist with a decade of experience bridging computational biology research and applied data science for fraud and identity solutions in Latin America. He holds a PhD in Computational Biology from USP and was a visiting researcher at the University of Chicago, where he built sequence-level gene transcription models and scaled analyses on Linux clusters. Alan has strong production experience in Python, R and OpenCV for image analysis, plus a software engineering background (Node.js/TypeScript, Java EE) that helps him translate research into robust clinical and enterprise systems. At ICESP he developed ML-driven clinical decision support tools that improved treatment selection, and now applies that rigor to risk analytics at LexisNexis. He’s comfortable coordinating cross-disciplinary teams and communicating technical findings to clinical and business stakeholders, a skill sharpened by teaching and project management roles. An uncommon blend of deep domain science and hands-on engineering, he delivers reproducible ML pipelines that connect biological insight to operational impact.
10 years of coding experience
4 years of employment as a software developer
Tecnico em Informática, Tecnologia da Informação, Tecnico em Informática, Tecnologia da Informação at Escola Tecnica Estadual de São Paulo
University of São Paulo
Visiting Student, Computational Biology, Visiting Student, Computational Biology at University of Chicago
Contributions:29 pushes, 1 branch in 3 years 8 months
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