Will Dean
Data Scientist
Summary
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RockstarWill Dean is a data scientist with five years of experience specializing in Bayesian statistics and geospatial analytics. He contributes to core open-source tooling, notably refining Gaussian Process APIs in the widely used PyMC probabilistic programming library by standardizing parameter names and improving tests and documentation. His work blends rigorous probabilistic modeling with pragmatic software engineering, ensuring research-grade methods are production-ready. Comfortable across back-end codebases, he focuses on clarity, consistency, and reproducible analytics. Based in the United States, he brings a practical emphasis on maintainable libraries that accelerate applied Bayesian workflows. An underappreciated strength is his attention to small API details that reduce user errors and improve long-term library ergonomics.
5 years of coding experience
Github Skills (8)
mcmc10
pymc10
probabilistic-programming10
python10
bayesian-inference10
statistic9
statistics9
variational-inference8
Programming languages (7)
Github contributions (5)
pymc-devs/pymc
Sep 2022 - Dec 2022
Bayesian Modeling and Probabilistic Programming in Python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:70 reviews, 6 commits, 14 PRs in 3 months
Contributions summary:Will primarily focused on refactoring and standardizing Gaussian Process (GP) parameters within the PyMC library. Their contributions involved renaming the 'noise' parameter to 'sigma' for API consistency and updating related test cases. They implemented code changes within the `gp.py` and `test_gp.py` files. The user also addressed documentation improvements for the `join_nonshared_inputs` function.
pythonbayesian-inferencestatistical-inferencemachine-learningprobabilistic-programming
wd60622/pymc-marketing
Mar 2023 - Jun 2024
Bayesian marketing toolbox in PyMC. Media Mix, CLV models and more.
Contributions:132 pushes, 42 branches in 1 year 3 months
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