About

Tyler is a data scientist and software developer specializing in sports analytics and predictive modeling. A Computer Science graduate from California Polytechnic State University San Luis Obispo, he discovered his passion for sports analytics early on, successfully developing NFL and NBA player prop prediction models that funded his college expenses.

His professional journey began at PricewaterhouseCoopers, where he built data solutions and business applications. Following his passion for sports analytics, he then joined Swish Analytics, where he currently supports football products, manages machine learning infrastructure, and leads documentation efforts.

With over 5 years of experience spanning consulting and startups, Tyler leverages advanced machine learning techniques and distributed computing to develop innovative solutions. He has successfully implemented various projects ranging from real-time analytics dashboards to sophisticated prediction models that have helped organizations make data-driven decisions.

Beyond his technical capabilities, Tyler is passionate about making complex data accessible and meaningful. He combines his deep understanding of sports analytics with modern software development practices to create intuitive solutions that bridge the gap between raw data and actionable strategy.