Felipe Marcelino is a data scientist with a decade of professional experience and over six years focused on machine learning, statistical modeling, and production-grade data systems. He has delivered measurable impact across finance (fraud detection), retail (demand and pricing), industry 4.0 (steel quality), healthcare (computer vision for glaucoma), and energy/resource allocation using reinforcement learning. Comfortable in both Python and Scala ecosystems, Felipe builds end-to-end solutions—APIs, Kubeflow pipelines, and scalable Spark processing—that bridge research and production. At Nubank he improved fraud detection by 33% using graph features, and his consulting work applied RL and boosting models to complex operational problems like ship allocation and nationwide SKU forecasting. He holds a Master’s in Computer Science and pairs strong stakeholder communication with practical XAI to make models actionable for domain experts. Based in Greater Belo Horizonte, he combines academic rigor with hands-on software engineering to turn ambiguous business questions into deployed AI products.
10 years of coding experience
9 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at Universidade Federal de Minas Gerais
Contributions:5 pushes, 1 branch in 3 years 6 months
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