Quantitative Researcher - Prediction Markets, Quant Trading

Job description

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 inputs - Research and develop quantitative pricing, market-making, and risk models across sports, non-sports, player props, parlays, and correlated markets - Model cross-market dependencies, correlations, and portfolio effects, especially for combinatorial products such as parlays - Partner closely with traders to improve pricing logic, market coverage, and trading performance - Build frameworks for backtesting, simulation, and model validation - Create tools to monitor model performance, calibration, P&L attribution, and live trading outcomes - Help define the tooling, workflow, and research standards for a new team ### Requirements: - Strong quantitative background in statistics, math, ML, economics, or a related field - Experience building models in trading, sports, betting, prediction markets, or similar domains - Strong Python/data skills and comfort owning data pipelines as well as modeling - Ability to move quickly from raw data to research insight to production-ready mode - High ownership, strong communication skills and comfortable with fast-paced high growth environment