Carl Dy
Data Scientist
Pasay, Philippines
Summary
🤩
Rockstar🎓
Top SchoolCarl Dy is a data scientist with a decade of hands-on experience blending machine learning, trading systems, and full-stack development from Pasay, Philippines. He brings an electronics engineering foundation (BS, De La Salle University) and specialized training in power electronics and data science, allowing him to bridge hardware-minded rigor with data-driven software solutions. Carl has contributed to open-source trading tooling—enhancing fastquant’s notification bot and live-trading hooks—demonstrating a knack for practical integrations that improve user workflows. His work shows attention to production-readiness: refactoring notification logic into reusable modules and producing demo notebooks that clarify proof-of-concept value. Comfortable across the stack, he focuses on making ML systems easier to operate in live environments rather than just in research notebooks. Colleagues would describe him as a pragmatic engineer who converts complex trading and data problems into clean, deployable features.
10 years of coding experience
Short Course, Data Science, Short Course, Data Science at NXTLVL AcademyBachelor of Science (BS), Electronics Engineering, Bachelor of Science (BS), Electronics Engineering at De La Salle UniversityPost Graduate Diploma, Power Electronics, Post Graduate Diploma, Power Electronics at Mapua Institute of TechnologyHigh School Diploma, High School Diploma at First Asia Institute of Technology and Humanities
Filipino, English
Github Skills (12)
machine-learning10
tradingview10
backtesting10
python10
algorithmic-trading10
data-science10
trading10
backtest10
api-design9
pandas9
api9
apim9
Programming languages (8)
Github contributions (5)
enzoampil/fastquant
Jul 2020 - Aug 2020
fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:3 reviews, 19 commits, 4 PRs in 1 month
Contributions summary:Carl primarily contributed to the `fastquant` repository by implementing and enhancing the notification bot functionality. They created a `trigger_bot` function to execute custom scripts and added parameters to the `BaseStrategy` class for live trading and date tracking. The user also created a demo notebook illustrating the proof of concept for the notification scheme, further demonstrating their focus on integrating external scripts and improving the user experience. The user also refactored the `trigger_bot` function to a separate module.
pythonfinancestocksalgorithmic-tradinglines
ajdajd/fastquant
Jul 2020 - Mar 2021
fastquant — Backtest and optimize your trading strategies with only 3 lines of code!
Contributions:12 commits, 12 PRs, 17 pushes in 8 months
pythonbacktesting-trading-strategiesfinancestocksalgorithmic-trading
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