Jake Vanderplas
Software Engineer at Google
Oakland, California, United States
Summary
🤩
Rockstar🎓
Top SchoolJake Vanderplas is a software engineer with 15 years of experience building Python tools that make data scientists and researchers more productive, currently working on Google Colab. He holds a PhD in Astronomy and serves as a Senior Data Science Fellow at the University of Washington, with research roots in scalable array-based analytics for projects like LSST. A prolific open-source contributor and author of the Python Data Science Handbook and Whirlwind Tour notebooks, his work spans SciPy, scikit-learn, NumPy, JAX, matplotlib, and Jupyter. He brings deep numerical and algorithmic expertise — from adding advanced modes to sparse eigenvalue solvers and implementing Bayesian Blocks to optimizing sparse-array operations — while also improving documentation and notebook-driven workflows. Based in Oakland, he blends academic rigor with product-focused engineering to make complex data workflows interactive, reproducible, and easier to adopt.
16 years of coding experience
6 years of employment as a software developer
Master of Science (MS), Astronomy, Master of Science (MS), Astronomy at University of WashingtonBachelor of Science (BS), Physics, Bachelor of Science (BS), Physics at Calvin College
Stackoverflow
81,637reputation
5.3mreached
1,702answers
13questions
image
top-1%
pandas
top-1%
jit
top-5%
dataframe
top-5%
matplotlib
top-1%
boxplot
top-5%
Github Skills (103)
notebook10
sparse-array10
restructuredtext10
python10
testing10
ipython10
text-formatting10
exporter10
markdown10
charts10
scikit10
pandas10
sparse-matrix10
statistics10
rs10
Programming languages (20)
Github contributions (5)
jakevdp/PythonDataScienceHandbook
Aug 2016 - Oct 2021
Python Data Science Handbook: full text in Jupyter Notebooks
Role in this project:
Data Scientist
Data ScientistContributions:222 commits, 61 PRs, 191 pushes in 5 years 3 months
Contributions summary:Jake's commits indicate contributions to the Python Data Science Handbook repository, focusing on the implementation and documentation of machine learning concepts. The user's work included the addition of various code listings and example data to explain and illustrate core machine learning topics, and also making formatting improvements. The contributions spanned different chapters and examples.
pythonjupyter-notebookscipysciencedata-science
astroML/astroML
Oct 2012 - Sep 2018
Machine learning, statistics, and data mining for astronomy and astrophysics
Role in this project:Technical Writer & Documentation Specialist
Technical Writer & Documentation SpecialistContributions:223 commits, 15 PRs, 36 pushes in 5 years 11 months
Contributions summary:Jake's commits primarily focus on updates and improvements to the documentation of the astroML project. The contributions include cleaning up and updating code examples for web pages, reformatting documentation, adding chapter information, fixing formatting errors, and adding an image. The changes suggest an emphasis on improving the presentation and usability of the documentation for the project.
statisticspythonminingdata-scienceastrophysics
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