Paul Butler
Member Of Technical Staff at Modal
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolPaul Butler is a software engineer and former quant with 17 years of experience building infrastructure that makes browser-based apps feel native. Currently a Member of Technical Staff at Modal and previously the founder of Jamsocket, he specializes in server-side systems that accelerate rich web tooling. His background spans Google Search engineering and quantitative work at Two Sigma, bringing rigorous data-driven design and production-grade reliability to distributed systems. An active open-source contributor, he has improved libraries from API integrations to pandas-sklean interoperability, reflecting a habit of polishing developer ergonomics as well as performance. Trained in math and computer science at the University of Waterloo, he blends analytical depth with entrepreneurial product instincts.
17 years of coding experience
10 years of employment as a software developer
Bachelor of Math Math and computer science, Bachelor of Math Math and computer science at University of Waterloo
Stackoverflow
1,201reputation
146kreached
10answers
0questions
Github Skills (22)
python10
apidoc10
data-science10
testing10
scikit10
pandas10
facebook-graph-api10
machine-learning10
api10
http-request10
scikit-learn10
json9
documentation8
nginx6
jupyter-notebook6
Programming languages (18)
Github contributions (5)
scikit-learn-contrib/sklearn-pandas
Apr 2013 - Mar 2015
Pandas integration with sklearn
Role in this project:
Data Scientist
Data ScientistContributions:17 commits, 1 PR, 1 push in 1 year 10 months
Contributions summary:Paul primarily focused on integrating pandas with scikit-learn. Their contributions include writing tests, updating documentation for installation, and modifying the README to reflect the usage of the library. They also bumped the version number, updated pandas requirements, and implemented grid search capabilities. The user's work involved adapting cross-validation methods and refining the example code for clarity.
pythonsklearnmachine-learningscikit-learnpandas
jgorset/facepy
Sep 2011 - Sep 2011
Facepy makes it really easy to use Facebook's Graph API
Role in this project:Back-end Developer
Back-end DeveloperContributions:8 commits in 9 days
Contributions summary:Paul primarily focused on modifying the Facepy library to interact correctly with Facebook's Graph API. Their contributions involved adjusting how the `access_token` is passed in POST and DELETE requests, switching from adding parameters to the URL to using the `params` argument. The user also refactored the `get_all` function for paginated results into a more general `get` function and updated related unit tests. These changes aimed to improve the library's functionality and maintainability.
apifacebookgraphreallygraph-api
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