Chelsea L
Engineering Manager at Datadog
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolChelsea L is an engineering manager in New York with nine years of experience building and leading teams at Datadog, currently overseeing the Sensitive Data Scanner platform after progressing through roles from individual contributor to manager. She combines a strong foundation in mathematical optimization (University of Waterloo) with hands-on systems engineering across metrics storage, aggregation pipelines, and edge scanning. Chelsea has contributed to high-profile open-source projects like SciPy, where she focused on fixing linear programming issues and improving tests and documentation—an indicator of attention to numerical robustness and maintainable code. Her background includes internships at Google and Bridgewater, reflecting comfort with both ML/ads quality problems and finance-grade engineering. Known for candid communication and a willingness to connect people, she pairs technical depth with team-oriented leadership and pragmatic problem solving.
8 years of coding experience
6 years of employment as a software developer
Ontario Secondary School Diploma, Science, Ontario Secondary School Diploma, Science at Ontario Science Centre Science SchoolBachelor of Mathematics, Honours Co-op, Mathematical Optimization (Specialization in Operations Research; Minor in Computer Science), Bachelor of Mathematics, Honours Co-op, Mathematical Optimization (Specialization in Operations Research; Minor in Computer Science) at University of Waterloo
English, Chinese
Github Skills (9)
algorithm10
algorithms10
scipy10
optimisation10
python10
optimizers10
scientific-computing10
numpy10
optimization10
Programming languages (5)
Github contributions (5)
scipy/scipy
Jul 2019 - Oct 2019
SciPy library main repository
Role in this project:
Back-end Developer / Software Engineer
Back-end Developer / Software EngineerContributions:32 commits, 2 PRs, 22 comments in 3 months
Contributions summary:Chelsea focused on bug fixes and maintenance within the `scipy/scipy` repository, specifically targeting the `optimize` module. Their contributions primarily involved addressing issues related to linear programming (LP) problems, including tolerance issues and redundancy removal. They implemented test cases to validate the fixes and refactored code for consistency and clarity. The user also made changes to improve documentation and code structure.
scipypythonscientific-computing
rishiosaur/oss
Jan 2021 - Dec 2024
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Contributions:5 reviews, 2 PRs, 1 issue in 3 years 11 months
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