Summary
Renan Cortes is a data science leader and tenure-track statistics professor with nine years of industry and academic experience, combining a Ph.D. in Economics and a postdoc in Spatial Statistics from UC Riverside. He builds production-ready ML systems and recommendation engines using PySpark, Python, R, and cloud-native tools, and has led cross-functional teams at Sicredi and Agi. An active open-source core developer of PySAL and the main author of the Python segregation library, he bridges rigorous spatial/econometric research with practical BI and visualizationâauthoring public Shiny platforms like VisualizaDEE. Comfortable from low-level SQL and data lakes to reinforcement-learning bandits in production, he also teaches and develops curriculum, reflecting a rare mix of applied engineering, reproducible research, and public-sector analytics.
9 years of coding experience
13 years of employment as a software developer
Bachelorâs Degree Statistics, Bachelorâs Degree Statistics at Federal University of Rio Grande do Sul
Postdoctorate Spatial Statistics/Software Development, Postdoctorate Spatial Statistics/Software Development at University of California, Riverside
Doctor of Philosophy (Ph.D.) Economics, Doctor of Philosophy (Ph.D.) Economics at PontifĂcia Universidade CatĂłlica do Rio Grande do Sul
Masterâs Degree Statistics, Masterâs Degree Statistics at Universidade Federal de Minas Gerais
Portuguese, English