SEJAL DUA

Data scientist, software engineer, and hoops nerd, based in New York City.

What I Do

Hey! I'm Sejal, a data scientist based in NYC. I specialize in modeling work at the intersection of sports and tech. Currently, I am working on scheduling optimization at the NBA League Office.

Previously, I worked at Nike and IBM. I have a Master’s in Analytics from Georgia Tech and a dual Bachelor’s in Data Science and Biomedical Engineering from Tufts.

In my free time, you can find me running in Central Park, perfecting my guacamole recipe, playing rec softball, or enjoying a good Sumo orange.

Selected Work

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Postseason Scenarios

An interactive React app that computes every possible NBA postseason seeding outcome in the browser, with full tiebreaker resolution, swing game detection, and historical date navigation.

ReactTypeScript+3

SoleMate

A data-driven running shoe recommendation engine that matches runners with the best shoes from 300+ lab-tested options using nearest-neighbor search in biomechanical feature space.

Machine LearningD3.js+2

Markit Social

AI-driven social event marketplace connecting people with local events.

Mobile DevelopmentReact Native+1

Penciv

Full-stack engineering on a feelings journal app, the antithesis of social media. Built the emotion color system and a Spotify Wrapped-style analytics experience.

React NativePostgreSQL+2

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Writing

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Towards Data Science

Jet Sweep: Route Optimization to Visit Every NFL Team at Home

Solving a traveling salesman variant to find the optimal road trip through all 32 NFL stadiums.

Jun 2024·12 min

Towards Data Science

Optimizing Super Bowl Squares with Linear Programming

Turning a party game into an optimization problem with PuLP and historical score data.

Feb 2024·10 min

Towards Data Science

The Intersection of Geocoding and Art with OpenStreetMap and NetworkX

Generating street network visualizations as art prints using geospatial data.

Jan 2024·10 min

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