Matthew Wardrop
Senior Full Stack Data Scientist
San Jose, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMatthew Wardrop is a Senior Full Stack Data Scientist based in San Jose with 13 years of experience building scalable software frameworks that marry advanced mathematics and production engineering. At Netflix and previously Airbnb, he has led work across experimentation, causal inference, ML, data infrastructure, and API design, turning complex analytics into reliable, auditable systems. He brings a researcher’s rigor from a PhD in Quantum Information Theory and first-class honors in Mathematics and Physics to pragmatic software delivery. An active open-source contributor, he has improved testing and cross-platform deployment in notable projects like patsy and Airbnb’s Knowledge Repo, emphasizing reproducibility and developer experience. Colleagues rely on him to bring structure to ambiguous problem spaces and to make routine programmatic tasks transparent through reusable tools. He combines deep quantitative intuition with full-stack implementation skills to drive high-impact data products in production.
13 years of coding experience
2 years of employment as a software developer
Gosford High SchoolThe University of Sydney
Github Skills (27)
circular-progress-bar10
pytest10
python10
testing10
progress-view10
user-interface10
progress-indicator10
flask-ask10
progressdialog10
progress-bar10
flask10
javascript9
terminal-application9
ipython9
terminal-emulator9
Programming languages (13)
Github contributions (5)
airbnb/knowledge-repo
Aug 2016 - Dec 2018
A next-generation curated knowledge sharing platform for data scientists and other technical professions.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:21 releases, 128 commits, 202 PRs in 2 years 4 months
Contributions summary:Matthew's contributions primarily focused on improving the knowledge repository's functionality and user experience. They made significant changes to the user interface, including improvements to the feed and overall theming. The commits also involved backend work, such as implementing new authentication methods. Furthermore, the user enhanced the system's deployment capabilities, including changes for Windows support, and fixed critical bugs.
scientistsnext-generationdata-analysisdatadata-science
pydata/patsy
Sep 2021 - Oct 2022
Describing statistical models in Python using symbolic formulas
Role in this project:QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:6 releases, 6 reviews, 24 commits in 1 year 1 month
Contributions summary:Matthew primarily focused on migrating the project's testing framework from `nosetests` to `pytest`, updating existing tests and ensuring compatibility with the new framework. Their contributions involved modifying testing-related dependencies in `setup.py`, refactoring test files like `patsy/design_info.py` and `patsy/test_build.py`, and adjusting test code to align with `pytest` conventions. Furthermore, the user also made changes to properly close an rst file.
statisticspythonhypothesis-testingformulasstatistical
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.