Roy Wedge
Lead Software Engineer at DataCebo
Lawrence, Kansas, United States
Summary
🤩
Rockstar🎓
Top SchoolRoy Wedge is a Lead Software Engineer with 11 years of experience building and maintaining production-quality ML and data engineering systems, currently based in Lawrence, Kansas. He has led engineering efforts at Alteryx and Feature Labs and now guides technical delivery at DataCebo, combining hands-on coding with release and package management expertise. A core contributor and release maintainer for the Featuretools project and an active contributor to Alteryx's EvalML AutoML library, he focuses on improving usability, dependency management, and primitives for automated feature engineering. Roy brings a strong foundation from an MIT BS in Computer Science and Engineering and a track record of making open-source tooling more robust and easier to adopt. Notably, he pairs leadership responsibilities with detailed work on documentation and installation fixes that reduce friction for downstream users and maintainers.
11 years of coding experience
8 years of employment as a software developer
Bachelor of Science (BS) Computer Science and Engineering, Bachelor of Science (BS) Computer Science and Engineering at Massachusetts Institute of Technology
Stackoverflow
226reputation
3kreached
15answers
0questions
Github Skills (16)
pandas10
machine-learning10
feature-engineering10
automl10
python10
data-science10
numpy9
documentation9
scikit-learn9
scikit9
unit-testing9
nested-forms6
featuretools6
jupyter-notebook6
feature-extraction6
Programming languages (7)
Github contributions (5)
alteryx/featuretools
Oct 2017 - Jan 2023
An open source python library for automated feature engineering
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:57 releases, 611 reviews, 304 commits in 5 years 4 months
Contributions summary:Roy contributed to the development of the Featuretools library for automated feature engineering, specifically enhancing the handling of primitives. They refactored the `Compare` primitive, implemented new features such as an associative attribute, and simplified the logic for deep feature synthesis. The user also focused on improving the usability and functionality of existing features by modifying tests and implementing fixes related to custom primitive creation, particularly concerning kwargs and numeric data handling.
python-librarypythondata-scienceautomated-machine-learningmachine-learning
alteryx/evalml
Aug 2019 - Jan 2023
EvalML is an AutoML library written in python.
Role in this project:Data Scientist
Data ScientistContributions:11 reviews, 26 commits, 8 PRs in 3 years 5 months
Contributions summary:Roy primarily contributes to documentation updates and code modifications related to the EvalML AutoML library. Their work includes updating documentation across multiple files, including examples, release notes, and guides. They also fix installation issues, update dependencies, and remove constraints on package versions. Their involvement focuses on enhancing documentation, improving the library's usability, and ensuring the proper installation and compatibility of dependencies.
pythondata-sciencemodel-selectionoptimizationmachine-learning
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.