I tackle unforeseen and unsolved challenges every day, and I enjoy applying my training as a mathematician along with my Python programming skills to run experiments, analyse problems.
As a consultant based in the San Francisco Bay Area, I use open-source libraries from the Scientific Python ecosystem to build production-grade solutions for my clients. Over time, I've developed specialisations in Machine Learning, Deep Learning, Predictive Data Analysis, Natural Language Processing, and Open Source Development.
I'm a core contributor to scikit-learn, where
I collaborate with the core maintainers and other contributors to provide simple and
efficient tools for accurate data analysis and machine learning. As a member of
scikit-learn's Contributor Experience Team, I also help triage issues
and support new contributors in getting familiar with the codebase and contribution
process through discussions and pull request reviews.
Previously, I studied mathematics at the University of California, Davis, and Purdue University.
Hobbies
In my spare time, I enjoy reading books and listening to music (classical and rock and roll). I also like hanging out with cats.
Have We Met Before?
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