Bruno Belluomini is a data scientist based in São Paulo with eight years of experience building risk and optimization models that drive real-time credit decisions and operational improvements. He has led and mentored small teams at Creditas, designed experiments for unbiased data collection at Nubank, and contributed to credit and collections models across fintechs. Comfortable across the ML lifecycle, he pairs Python, SQL and cloud tooling (BigQuery, Databricks, Kubeflow, AWS) with production-aware engineering practices and occasional Scala. He has a background in civil engineering and technical programming, which informs his pragmatic approach to feature engineering and spatial-data solutions. Known for turning messy, unstructured sources into reliable data pipelines, he also organizes knowledge-sharing initiatives like meetups to lift team capabilities. Bruno combines product-minded impact with curiosity-driven experimentation to uncover non-obvious patterns that improve business outcomes.
8 years of coding experience
6 years of employment as a software developer
Bacharelado em Engenharia Engenharia Civil, Bacharelado em Engenharia Engenharia Civil at Universidade Estadual Paulista Júlio de Mesquita Filho
Técnico Informática com Ênfase em Programação, Técnico Informática com Ênfase em Programação at Etec Professor Basilides de Godoy
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