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

Quantitative Researcher - Prediction Markets, Quant Trading

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