Eli Feasley
Data Scientist
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolEli Feasley is a data scientist and former software engineer with 14 years of experience applying analytics, engineering, and legal training to advance abolitionist reforms and bolster public defense in New York. At Neighborhood Defender Service they built AI-driven scheduling and a 30-factor sentencing calculator, automated hundreds of hours of work, and created interactive dashboards and websites that shortened case assignment from days to minutes. Earlier, Eli led growth, personalization, and experimentation efforts at Khan Academy—authoring the platform’s first recommendation engine, running hundreds of A/B tests, and contributing front-end work to well-known open-source projects. With a JD from Yale and deep technical roots in CS research and machine learning, they uniquely bridge law, policy, and production ML systems. Colleagues rely on Eli not only for technical delivery but for securing funding, training practitioners, and translating complex data into actionable advocacy.
14 years of coding experience
6 years of employment as a software developer
Most of a Masters (.9M) Computer Science, Most of a Masters (.9M) Computer Science at The University of Texas at AustinDoctor of Law - JD, Doctor of Law - JD at Yale Law SchoolUMBC
English
Github Skills (5)
javascript10
html9
css9
jquery8
testing6
Programming languages (7)
Github contributions (5)
Khan/khan-exercises
Aug 2013 - Oct 2015
A (deprecated) framework for building exercises to work with Khan Academy.
Role in this project:
Front-end Developer
Front-end DeveloperContributions:5 commits, 2 pushes in 2 years 1 month
Contributions summary:Eli primarily contributed to the front-end aspects of the Khan Academy exercises framework, specifically focusing on the implementation of new features like "worked example" functionality and assessment A/B tests. Their work included modifying the `interface.js` file to handle user interactions with new buttons and events, along with adjustments to the CSS for visual presentation. Additionally, they worked on disabling hint detection to address reported issues.
khan-academy
cutealism/so-you-want-to-fight-the-state
Nov 2016 - Dec 2022
Contributions:19 commits, 1 PR, 19 pushes in 6 years 1 month
cssfighthow-to-guide
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