Joel Ricci-lopez is a Senior Data Scientist with eight years of experience applying machine learning and data engineering to biological and commercial problems, currently driving customer analytics and automation at AB InBev. He builds end-to-end solutions—RFM and cohort segmentation, market-basket models, and automated SKU matching—using Python, PySpark, Azure Databricks, and Power BI to turn heterogeneous data into actionable sales and retention insights. Trained as a PhD in Biomathematics/Bioinformatics, he bridges high-performance scientific computing (molecular dynamics, HPC collaborations) and production ML, bringing rigorous research methods to business use cases. He has taught and mentored students in simulation and data analysis and completed intensive programs in deep learning and scientific software engineering, reflecting a strong foundation in both theory and reproducible workflows. Based in Ensenada, Mexico, he combines domain expertise in biological sciences with practical experience shipping analytics at scale. An often-overlooked strength is his hands-on background in web development and tooling, which helps him deliver polished dashboards and reproducible pipelines.
7 years of coding experience
3 years of employment as a software developer
Universidad Nacional Autónoma de México (UNAM)
AI Product Manager Artificial Intelligence, AI Product Manager Artificial Intelligence at Udacity
Licenciatura en Biología, Licenciatura en Biología at Universidad del Mar (MX)
Doctor of Philosophy - PhD Biomathematics Bioinformatics and Computational Biology, Doctor of Philosophy - PhD Biomathematics Bioinformatics and Computational Biology at Centro de Investigación Científica y de Educación Superior de Ensenada
Improving Structure-Based Virtual Screening with Ensemble Docking and Machine Learning
Contributions:224 commits, 2 PRs, 98 pushes in 1 year
ensemble-dockingdockingscreeningensembledocker
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