Francisco Caio is a Lead Data Scientist and computer engineer with a Master’s degree and eight years of experience building production-grade ML systems and scalable software. He has led technical teams in startups and at major banks, architecting cloud-native decisioning platforms that boosted revenue, retention, and time-to-value while migrating projects to modern in-house tooling. His research blends reinforcement learning and sentiment analysis for financial trading, with multiple publications and contributions to Towards Data Science, reflecting a strong bridge between academic rigor and business impact. At Banco Itaú he delivered real-time ML APIs, observability, and deploy automation that materially improved availability and operational cadence. Now at Nubank he focuses on predictive models for corporate credit, continuing to pair innovation in modeling with pragmatic delivery. Colleagues note his rare mix of hands-on engineering, research-driven curiosity, and measurable business outcomes.
8 years of coding experience
12 years of employment as a software developer
Master of Science - MS, Computer Engineering, Master of Science - MS, Computer Engineering at Escola Politécnica da USP
Research project implementation for the ICAIF'21 publication and Master's Thesis. ITS-SentARL => Intelligent Trading Systems: A Sentiment-Aware Reinforcement Learning Approach
Contributions:56 commits, 2 PRs, 41 pushes in 2 years 5 months
Web Crawler for financial news with scientific research purposes.
Contributions:29 commits, 4 PRs, 68 pushes in 2 years 5 months
financialscrapyweb-crawlerscientificcrawler
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