Max Kanter
Creator
Boston, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolMax Kanter is a creator and engineer with 14 years of experience building data-driven products and open-source tooling, currently focused on GridStatus.io to bring AI and real-time insights to the electrical grid. He co-founded Feature Labs (acquired by Alteryx), led Alteryx’s cloud AutoML engineering organization, and scaled teams while shipping production AutoML for thousands of developers. An MIT-trained software and data scientist, he has contributed to influential open-source projects like Featuretools and EvalML—adding production-ready primitives, domain-specific fraud detection, and robust documentation and testing. Max blends hands-on engineering, product leadership, and research as a visiting scholar at MIT, and brings a knack for turning complex ML research into practical, widely used software.
13 years of coding experience
13 years of employment as a software developer
Master of Engineering (MEng), Computer Science, 5.0 GPA, Master of Engineering (MEng), Computer Science, 5.0 GPA at Massachusetts Institute of TechnologyHigh School Diploma, High School Diploma at New Trier High School District
Stackoverflow
2,006reputation
32kreached
66answers
2questions
Github Skills (19)
python10
evaluation10
data-science10
scikit10
machine-learning10
feature-engineering10
fraud-detection10
eval10
automl10
scikit-learn10
automated-machine-learning10
documentation10
pandas9
unit-testing9
api-design8
Programming languages (5)
Github contributions (5)
alteryx/featuretools
Sep 2017 - Nov 2020
An open source python library for automated feature engineering
Role in this project:
Data Scientist
Data ScientistContributions:9 releases, 12 reviews, 117 commits in 3 years 2 months
Contributions summary:Max primarily contributed to the `featuretools` repository by updating documentation, including the changelog and API references, and releasing new versions. Their work involved fixing bugs and implementing new features related to automated feature engineering, like the "last time index" and handling of categorical and ID variable types. They also made improvements to existing primitives and added tests, which contributed to the stability and functionality of the library.
python-librarypythondata-scienceautomated-machine-learningmachine-learning
alteryx/evalml
Jul 2019 - Dec 2019
EvalML is an AutoML library written in python.
Role in this project:Data Scientist
Data ScientistContributions:7 reviews, 101 commits, 3 PRs in 4 months
Contributions summary:Max implemented a `FraudDetection` class within the `evalml` library, demonstrating expertise in building domain-specific objective functions. The code defines the `FraudDetection` class with methods for fitting, predicting, and scoring, showcasing an understanding of machine learning model evaluation. The changes include adding the `FraudDetection` class and integrating it into the `evalml` package, including a test file. They also modified the `Classifier` class to incorporate the new `FraudDetection` for scoring.
pythondata-sciencemodel-selectionoptimizationmachine-learning
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