Summary
Flávio Barros is an experienced data scientist and educator based in São Paulo with over a decade working at the intersection of recommender systems, data mining, and statistical learning. As a teacher at IFSP and a PhD candidate in statistics, he applies machine learning and predictive modeling to real-world recommendation projects with EMBRAPA and has international research experience as a visiting student at the University of Alberta. Proficient in R and Python, he maintains a public portfolio of R-focused data science work and repositories on GitHub and shares insights on a long-running blog about mining, ML and statistics. His background in physics and electronics gives him a practical, experimental approach to modeling and feature engineering, while extensive Linux experience underpins his reproducible research workflows.
12 years of coding experience
Doutorado, Estatística, 5, Doutorado, Estatística, 5 at Instituto de Ciências Matemáticas e de Computação (ICMC)
undergrad, Statistics, undergrad, Statistics at Universidade Estadual de Campinas
English, Portuguese, Spanish