Mollie Pettit
Developer Relations Engineer - AI Platform
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMollie Pettit is a developer relations and product leader with 11 years of experience building developer ecosystems, product education, and data visualization programs for companies from startups to Google. She has a track record of turning community insight into product impact—growing the Data Visualization Society to 19,000+ members, launching the Outlier conference, and adding thousands of engaged users to platforms like Great Expectations and Dagster. A former data scientist and visualization engineer, Mollie combines hands-on technical chops (D3.js, Python, Jupyter) with cross-functional leadership, hiring and scaling teams, and running large events that drive adoption. Her open-source contributions include educational notebooks for data-for-good projects, reflecting a focus on practical, reproducible tooling and onboarding. Based in San Francisco, she balances deep product instincts with a curiosity for AI—recently completing an intensive deep learning course—while staying energized by partner dancing and long-distance cycling.
11 years of coding experience
11 years of employment as a software developer
Bachelor of Science (BS), Mathematics, 3.7 GPA, Bachelor of Science (BS), Mathematics, 3.7 GPA at West Virginia UniversityData Science with Python, Data Science, Data Science with Python, Data Science at ThinkfulMaster of Science (MS), Geological and Earth Sciences/Geosciences, 3.7 GPA, Master of Science (MS), Geological and Earth Sciences/Geosciences, 3.7 GPA at Stanford University
English
Github Skills (6)
pandas10
jupyter-notebook10
python10
data-science10
numpy9
machine-learning8
Programming languages (6)
Github contributions (5)
dssg/hitchhikers-guide
May 2018 - Jun 2018
The Hitchhiker's Guide to Data Science for Social Good
Role in this project:
Data Scientist
Data ScientistContributions:84 commits, 1 PR, 72 pushes in 28 days
Contributions summary:Mollie contributed to the project by adding and editing a Jupyter notebook that provides a test for the software setup, ensuring all necessary Python packages are installed and functioning correctly. This includes checking the installation of libraries such as NumPy, Pandas, and Scikit-learn. Furthermore, the user updated a Python tutorial notebook focused on data exploration and analysis, and the commits also included merging branch changes. These actions point to active participation in educational and analytical aspects.
data-sciencedssgtrainingmachine-learning
molliemarie/D3Workshops
Dec 2018 - Mar 2019
Contributions:55 commits, 49 pushes, 1 branch in 3 months
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