Teams at Swish Analytics

Investigate production incidents using raw real-time data, identify root causes, and recommend resolutions. Build statistical system-health metrics, descriptive reports, and repeatable investigation tooling. Analyze event-driven systems during live sports events, work independently on ambiguous problems, and collaborate with data science, engineering, and trading teams. Develop and maintain production software using Python and Rust.

Manage sportsbook risk and profitability through positive expected value decisions, maintain accurate depth charts, adjust prematch and in-play markets, research verified sports news, and analyze betting trends to drive quantifiable trading actions. Requires at least three years of online sportsbook in-game experience, strong odds and statistical knowledge, familiarity with major North American sports, and flexible availability for nights, weekends, and holidays.

Manage NHL and multi-sport betting risk, pricing, exposure, and live in-play markets. Monitor depth charts, news, betting trends, line movement, and game events to make data-driven trading decisions. Build and test betting models, calculate odds and expected value, and improve profitability. Requires flexible scheduling, including nights, weekends, and holidays, with collaboration across trading and data science teams.