White Swan Data

Data-driven betting models; liquidity provider

Football Trader

Prop & Hedge Fund TradingUpdated on Nov 13

Full-timeLondon, UKNo salary listedIn-person

About the Job

Requirements

Strong mathematical background; a degree in Mathematics, Statistics, Physics, Engineering, or a related field is preferred.
Comprehensive knowledge of football, including leagues, teams, and strategies.
Strong analytical skills and attention to detail.
Ability to make quick decisions under pressure.
Proficiency in Microsoft Excel and/or basic data analysis tools.

Responsibilities

Monitor football betting markets, track odds movements, and identify trading opportunities.
Analyse live and historical football data to inform trading strategies.
Adjust prices in response to market trends and real-time events, including goals, injuries, and substitutions.
Collaborate with analysts to refine trading models and improve market predictions.
Maintain focus and accuracy in high-pressure, fast-paced environments, particularly during live matches.
Stay informed about football leagues, teams, players, and trends to gain a competitive edge.
Work over the weekend during football season and at least two evening shifts, finishing past 10:30 pm.

Desired Qualifications

Prior trading experience is a plus.
Experience with statistical programming languages such as Python or R.
Knowledge of betting markets or prior experience in a trading environment.
Understanding of predictive modeling and probability theory.
Passion for football analytics and/or sports betting.

White Swan Data is a small but rapidly growing team of mathematicians, data scientists and software engineers who are constantly striving to refine world class probability models while also researching and deploying new ones. Our work bridges three domains, each challenging in its own right - iGaming, quantitative research and software development.

As a Football Trader, you will monitor and manage betting markets, analyse live football data, and make decisions to optimize trading outcomes. This role combines a strong mathematical aptitude with a deep understanding of football dynamics. Prior trading experience is not required but will be considered a plus.

You will be expected to work over the weekend during football season and at least 2 evening shifts (finish past 10:30 pm).

This role will reward individuals who are curious, hungry for learning and value attention to detail.

Monitor football betting markets, track odds movements, and identify trading opportunities.
Analyse live and historical football data to inform trading strategies.
Adjust prices in response to market trends and real-time events (e.g., goals, injuries, substitutions).
Collaborate with analysts to refine trading models and improve market predictions.
Maintain focus and accuracy in high-pressure, fast-paced environments, particularly during live matches.
Stay informed about football leagues, teams, players, and trends to gain a competitive edge.

Essential:

Strong mathematical background (degree in Mathematics, Statistics, Physics, Engineering, or a related field preferred).
Comprehensive knowledge of football, including leagues, teams, and strategies.
Strong analytical skills and attention to detail.
Ability to make quick decisions under pressure.
Proficiency in Microsoft Excel and/or basic data analysis tools.

Desirable:

Experience with statistical programming languages (e.g., Python, R).
Knowledge of betting markets or prior experience in a trading environment.
Understanding of predictive modeling and probability theory.
Passion for football analytics and/or sports betting.

About the Company

White Swan Data

Data-driven betting models; liquidity provider

White Swan Data is a London-based firm that builds data-driven betting models to identify opportunities in iGaming and prediction markets. It provides mathematics and data-led services to price risk and develop betting strategies, and acts as a market maker and liquidity provider for prediction exchanges and related platforms. It quotes prices, absorbs event risk, and supplies liquidity to deepen markets, sometimes handling a large share of activity on secondary exchanges. Its team of mathematicians, data scientists, and software engineers builds the infrastructure to support gambling and trading services, aiming to deliver reliable liquidity and scalable trading systems for clients.

Company size: 51-200
Company stage: Not listed
Total funding: Not listed
Headquarters: London, United Kingdom
Founded: 2019

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