Quantitative Researcher - Prediction Markets, Quant Trading

Role overview

This position sits on a newly formed quantitative research group dedicated to prediction markets, with a focus on pricing, market-making, and risk modeling. The role is very hands-on and spans the full workflow: preparing data, conducting research, building models, and working closely with trading teams. The scope includes both sports-related and non-sports event markets, along with multiple contract structures such as single-outcome markets, player props, and parlays.

What you will do

• Develop the data layer and convert raw information into inputs that can be used for pricing.
• Design and improve quantitative models for pricing, market-making, and risk across sports, non-sports, player props, parlays, and correlated markets.
• Analyze dependencies between markets, correlations, and portfolio-level effects, with particular attention to combinatorial products like parlays.
• Work side by side with traders to strengthen pricing rules, expand market coverage, and enhance trading results.
• Create testing frameworks for backtesting, simulation, and validation of models.
• Build monitoring tools to track model quality, calibration, P&L contribution, and live trading performance.
• Contribute to the setup of the team’s tooling, operating workflow, and research practices.

What we are looking for

• A strong quantitative foundation in statistics, mathematics, machine learning, economics, or a closely related discipline.
• Prior experience building models in trading, sports, betting, prediction markets, or comparable environments.
• Solid Python and data engineering capabilities, including comfort with both pipelines and modeling work.
• Ability to move efficiently from raw data analysis to research conclusions to production-ready models.
• Strong accountability, clear communication, and the ability to thrive in a fast-moving, high-growth setting.

Additional information

The company may use AI-based tools to review resume and CV details against the position requirements. These tools are intended to assist the recruitment team by offering recommendations, but final decisions remain with human reviewers. If you want more information about how personal data is processed, you may contact the company directly.