Quantitative Sports Trader

Susquehanna International Group · Dublin

Overview

This is a trading and quantitative strategy role focused primarily on trading on prediction markets. You will make fast, informed trading decisions while developing and maintaining the quantitative models, data pipelines, and tools that drive trading performance. The role blends hands-on trading with quantitative research, model development, and product ownership — ideal for someone who thrives at the intersection of markets, analytics, and technology.

In this role, you will:

Trade using in-house models, data-driven insights, and automated tools to maximize expectancy and meet business objectives.
Take ownership of trading strategies and associated models — designing, implementing, and refining logic for execution, pricing, and market-making.
Collaborate closely with quantitative researchers and engineers to identify, design, and deploy model enhancements, data features, and trading infrastructure improvements.
Perform post-trade analysis of decisions, model performance, and market behavior to inform strategy development and model calibration.
Identify opportunities in prediction market dynamics — pricing inefficiencies, liquidity behavior, or reaction times — to strengthen the team’s edge.
Drive innovation in trading methodology, tooling, and data usage across the trading and quantitative teams.

What we're looking for

Bachelor’s degree or higher in a technical or quantitative discipline (e.g., Mathematics, Statistics, Computer Science, Physics, Economics).
Deep domain expertise and passion for sports such as Football, Soccer or Golf, including understanding of tactical, statistical, and market aspects of the sport and direct experience trading them.
Demonstrated ability in Python, including strong experience with data manipulation (Pandas, NumPy), statistical analysis, and automation.
Experience integrating data and models into production trading workflows is a strong plus.
Exceptional quantitative reasoning, analytical, and problem-solving skills.
Experience trading or modelling in fast-moving, competitive markets (prediction markets, exchanges, or similar).
Ability to operate across both trading and quantitative research, bridging analytical insight with execution.
Comfort taking product ownership — defining priorities, implementing features, and improving workflows end-to-end.
Strong communication skills, both for collaboration and articulating decision rationale.
Flexibility with working hours to align with global game/match/tournament schedules.

If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.

Bachelor’s degree or higher in a technical or quantitative discipline (e.g., Mathematics, Statistics, Computer Science, Physics, Economics).
Deep domain expertise and passion for sports such as Football, Soccer or Golf, including understanding of tactical, statistical, and market aspects of the sport and direct experience trading them.
Demonstrated ability in Python, including strong experience with data manipulation (Pandas, NumPy), statistical analysis, and automation.
Experience integrating data and models into production trading workflows is a strong plus.
Exceptional quantitative reasoning, analytical, and problem-solving skills.
Experience trading or modelling in fast-moving, competitive markets (prediction markets, exchanges, or similar).
Ability to operate across both trading and quantitative research, bridging analytical insight with execution.
Comfort taking product ownership — defining priorities, implementing features, and improving workflows end-to-end.
Strong communication skills, both for collaboration and articulating decision rationale.
Flexibility with working hours to align with global game/match/tournament schedules.

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