Summary
Rafael Katopodis is a Data Scientist based in Rio de Janeiro with 10 years of experience applying ML to personalization and recommender systems. He holds a B.Sc. (magna cum laude) and an M.Sc. in Artificial Intelligence from UFRJ, and has built and productionized collaborative filtering and next-basket recommenders for a B2B platform serving nearly a million users. His work spans exploratory analysis, model development in PyTorch and scikit-learn, and deployment on Azure Databricks with MLflow, with impacts measured via online A/B experiments. Curious beyond recommendation, he explores sequential decision-making with reinforcement learning and compact neural architectures like n-tuple networks, reflecting a research-minded approach to pragmatic engineering.
10 years of coding experience
4 years of employment as a software developer
M.Sc., Artificial Intelligence, M.Sc., Artificial Intelligence at Federal University of Rio de Janeiro
English, Portuguese