Quantitative Sports Trader

Role overview

This position sits at the crossroads of trading, quantitative research, and technology, with a strong focus on prediction markets. The successful candidate will make quick, well-informed trading calls while also building and improving the quantitative models, data workflows, and tools that support trading outcomes. It is a hands-on role for someone who enjoys working across markets, analytics, and software.

What you will do

• Use internal models, data-led insights, and automated tools to place trades that improve expected value and support business goals.
• Own trading approaches and the related models, including the design, build, and refinement of execution logic, pricing methods, and market-making systems.
• Partner with quantitative researchers and engineers to spot opportunities for better models, new data features, and stronger trading infrastructure.
• Review completed trades and assess decision quality, model accuracy, and market patterns to improve strategy and calibration.
• Look for inefficiencies in prediction markets, such as pricing gaps, liquidity patterns, or response delays, that can create an edge.
• Contribute new ideas to trading methods, tooling, and the use of data across the wider trading and quantitative teams.

What we are looking for

The role calls for a candidate with a technical or quantitative background and strong interest in sports markets, especially football, soccer, or golf. You should be comfortable combining analysis with execution and able to work in fast-paced, competitive environments.

Eligibility and background

• A bachelor’s degree or higher in a quantitative or technical field such as mathematics, statistics, computer science, physics, or economics.
• Solid knowledge of and genuine enthusiasm for sports like football, soccer, or golf, including tactical, statistical, and market-related understanding, plus direct trading experience in these sports.
• Strong Python skills, especially with Pandas, NumPy, statistical analysis, and automation.
• Experience bringing data and models into live trading processes is an added advantage.
• Excellent quantitative thinking, analysis, and problem-solving ability.
• Background in trading or modelling within fast-moving and competitive markets, such as prediction markets or exchanges, is preferred.
• Ability to move fluidly between trading and quantitative research work.
• Comfort with product ownership, including setting priorities, delivering features, and improving workflows from end to end.
• Strong communication skills for teamwork and explaining trade or strategy decisions clearly.
• Willingness to work flexible hours to match global game, match, and tournament schedules.

Additional information

If you are a recruitment agency interested in partnering, please contact the company directly at recruiting@sig.com. Resumes or referrals sent without a signed agreement will not qualify for an agency fee.