Benjamin Del Mundo is a Machine Learning Engineer with nine years of hands-on experience building and refining ML and data science projects from the Philippines. He contributes to open-source tooling for algorithmic trading—refactoring and improving the fastquant codebase to make backtesting and strategy development more maintainable and reliable. Comfortable across the full stack of ML workflows, he emphasizes clean, well-formatted code and pragmatic updates to indicators, strategies, and data modules. A product-minded engineer with roots in computer games and programming from Ateneo de Manila, he blends practical engineering discipline with curiosity for applied ML in finance and data-driven products.
9 years of coding experience
High school, Computer Games and Programming Skills, High school, Computer Games and Programming Skills at Ateneo de Manila University
fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!
Role in this project:
Full-stack Developer
Contributions:10 reviews, 38 commits, 15 PRs in 4 months
Contributions summary:Benjamin primarily refactored existing code, primarily focused on improving code formatting and structure. They used the black code formatter to reformat existing Python files. Further refactoring involved updates to disclosures, indicators, and strategies across several modules, and included the refactoring of data modules. In addition, the user updated strategy implementations in the fastquant project.
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