Max Woolf
Senior Data Scientist
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMax Woolf is a Senior Data Scientist based in San Francisco with 13 years of experience turning messy data into clear, actionable stories. After starting in software QA at Apple, he transitioned to data roles at BuzzFeed where he progressed from contract Data Scientist to senior lead, blending product-minded analysis with production ML. He maintains the popular minimaxir open-source projects—ranging from GPT-2 tooling (gpt-2-simple, aitextgen, textgenrnn) to useful utilities like the Big List of Naughty Strings—which reflect a practical focus on reproducible model training and robust data pipelines. Max combines strong visualization chops (ggplot2 and interactive plotting) with hands-on ML engineering, feature engineering, and automation work, and he often publishes notebooks that make social media and engagement data easy to explore. Notably, his tooling emphasizes usability—features like nucleus sampling, Drive integration, and automated model/code generation show a pragmatic drive to lower barriers for others to train and deploy text models.
13 years of coding experience
12 years of employment as a software developer
Bachelor of Science - BS Computing and Information Technology, Bachelor of Science - BS Computing and Information Technology at Carnegie Mellon University
Stackoverflow
1reputation
0reached
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Github Skills (47)
text-generation10
data-visualizations10
transformers10
json10
tokenize10
xgboost10
pytorch10
python10
image-processing10
r10
scikit10
pandas10
machine-learning10
data-visualisation10
rnn-model10
Programming languages (10)
Github contributions (5)
minimaxir/textgenrnn
Jun 2017 - Jul 2020
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
Role in this project:
ML Engineer
ML EngineerContributions:12 releases, 136 commits, 26 PRs in 3 years 1 month
Contributions summary:Max implemented a text-generating neural network using Keras and TensorFlow. Their contributions focused on defining the model architecture, incorporating embedding layers, and integrating recurrent neural networks (LSTMs). The user also worked on training the model, including data encoding and the implementation of a learning rate scheduler, as well as adding functionalities to generate text.
neural-networkkerasdeep-learningtext-generationtensorflow
minimaxir/big-list-of-naughty-strings
Aug 2015 - Apr 2021
The Big List of Naughty Strings is a list of strings which have a high probability of causing issues when used as user-input data.
Role in this project:Back-end Developer
Back-end DeveloperContributions:135 commits, 110 PRs, 123 pushes in 5 years 9 months
Contributions summary:Max primarily contributed to the project by creating and updating a Python script (`txt_to_json.py`) to convert a text file of "naughty strings" into a JSON format. Their work included modifying the script to handle edge cases such as removing comments, inserting empty strings, and addressing backslash issues to ensure valid JSON output. The user also merged in code from other contributors, and addressed merge conflicts in the main text file.
naughty-stringsnaughtyinput-datastringsjavascript
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