We’re building a new quantitative research team focused on pricing, market-making, and risk models for prediction markets. This is a highly hands-on role for someone who can operate end-to-end: data engineering, research, modeling, and close collaboration with traders, across sports and non-sports event markets and a range of contract types, including single-outcome markets, player props, and parlays.Responsibilities:Build data foundation, transform raw data into pricing inputsResearch and develop quantitative pricing, market-making, and risk models across sports, non-sports, player props, parlays, and correlated marketsModel cross-market dependencies, correlations, and portfolio effects, especially for combinatorial products such as parlaysPartner closely with traders to improve pricing logic, market coverage, and trading performanceBuild frameworks for backtesting, simulation, and model validationCreate tools to monitor model performance, calibration, P&L attribution, and live trading outcomesHelp define the tooling, workflow, and research standards for a new teamRequirements:Strong quantitative background in statistics, math, ML, economics, or a related fieldExperience building models in trading, sports, betting, prediction markets, or similar domainsStrong Python/data skills and comfort owning data pipelines as well as modelingAbility to move quickly from raw data to research insight to production-ready modeHigh ownership, strong communication skills and comfortable with fast-paced high growth environment
