Machine Learning Engineer
Jaedon Cox
Computer Science student at UT Arlington. I design and deploy machine learning pipelines, with a focus on sports analytics and data-driven decision making.
Who I am
I am a computer science student at UT Arlington focused on machine learning and data systems. I build automated pipelines and predictive models for real-world data, with an emphasis on sports analytics and market inefficiencies.
Currently, I am optimizing my MLB prediction models to improve performance against sportsbook lines by refining features, tuning models, and evaluating results across large sets of daily prop data.
When I'm not at my keyboard, I'm usually watching the Texas Rangers or at the gym. I like staying engaged with sports both as a fan and through an analytical lens, often thinking about how data and performance connect.
The problem
Sports betting markets are often imperfect, with lines that don't always reflect true player performance or underlying data. This creates opportunities where probabilities implied by the market may differ from actual outcomes.
What I built
Zentrikz is an end-to-end machine learning system that automates data ingestion and feature engineering, runs predictive models across multiple player prop types, and generates daily outputs at scale.