Alan Barzilay is a data scientist with nine years of experience combining academic rigor (MSc in Computer Science from IME-USP) and production impact in finance and research settings. He has driven measurable results—improving a key credit-scoring KPI by 20% at Banco PAN—while building MLOps practices and a reusable library to cut development overhead and boost reproducibility. His background spans interdisciplinary projects from malaria transmission mapping at Oxford to modernizing CI and integration tests for Linux Foundation projects during Google Summer of Code. An active open-source contributor, he enhanced the popular pipreqs tool by removing Python 2 cruft, adding dynamic versioning and richer test coverage, showing a practical focus on maintainability. Based in São Paulo, Alan blends machine learning, software engineering and domain pragmatism to deliver robust, production-ready models and tooling.
9 years of coding experience
1 year of employment as a software developer
Electrical Engineering, Electrical Engineering at Escola Politécnica da USP
FAPESP BEPE MSc Research Program, Computer Science, FAPESP BEPE MSc Research Program, Computer Science at Delft University of Technology
Master of Science - MSc, Computer Science, Machine Learning, Software Engineering, Natural Language Processing, Master of Science - MSc, Computer Science, Machine Learning, Software Engineering, Natural Language Processing at Instituto de Matemática e Estatística - Universidade de São Paulo (IME-USP)
Ensino Médio, Ensino Médio at Colégio Bandeirantes
pipreqs - Generate pip requirements.txt file based on imports of any project. Looking for maintainers to move this project forward.
Role in this project:
Full-stack Developer
Contributions:1 release, 74 reviews, 31 commits in 1 year 10 months
Contributions summary:Alan contributed to the project by implementing new features, including the "--no-pin" parameter and dynamic versioning schemes, suggesting enhancements to the core functionality of generating requirements.txt files. They also worked on improving the test suite, adding new test cases and addressing existing tests. Their work extended to code cleanup and refactoring, including the removal of Python 2 specific components, to improve overall maintainability and ensure project compatibility with modern Python versions.
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