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Football Trader

Posted March 05, 2026
Full Time

Job Overview

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.

Key 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 (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.

Skills, Knowledge and Expertise

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.

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