Quantitative Sports Trader – European & Asian MarketsLocation:Europe (working hours aligned with European and Asian sporting markets)
Experience:2-8 years
Technology:Python and/or C#
Markets:Sports pricing, prediction markets, betting exchanges, in-play trading
Quantitative Sports Trader opportunity with a specialist sports pricing and trading business applying quantitative modelling, trading and risk management techniques to sports markets.
The team is expanding its European and Asian market coverage, with a focus on pricing and trading sports events across pre-match and in-play markets. The successful candidate will combine statistical modelling, market analysis and commercial decision-making to identify opportunities and manage risk.
The role sits between a sportsbook trader, quantitative researcher and financial-market trader. The successful candidate will help price and trade European and Asian sporting markets, improve models and develop the systems used to manage live exposure.
Responsibilities
- Price pre-match and in-play sports markets using quantitative models and market information.
- Develop and improve probabilistic pricing models.
- Identify mispriced markets and trading opportunities across sportsbooks, exchanges and prediction markets.
- Manage positions, limits, correlations and event-level exposure.
- Monitor live events and react to new information.
- Analyse historical results, model performance and calibration.
- Automate and improve repeatable parts of the pricing and trading process.
- Work closely with researchers and developers to improve data, execution and risk systems.
- Provide trading coverage across European and Asian sporting hours.
The strongest candidates will typically have:
- Experience within a sportsbook trading team, betting exchange, prediction market or sports trading environment.
- Experience pricing or trading sports markets, either pre-match or in-play.
- Strong probability, statistical reasoning and quantitative modelling skills.
- Understanding of odds, implied probability and expected value.
- Experience managing exposure, limits or commercial risk.
- Python, C# or comparable programming experience.
- Ability to distinguish model accuracy from trading profitability.
- Interest in building and improving trading processes rather than simply operating existing systems.
Candidates from quantitative sportsbook teams, sports market-making businesses, prediction markets, sports-data providers or quantitative trading environments with direct sports exposure may be highly relevant.
#J-18808-Ljbffr
South East England
Any
Posted 4 days ago by Harrington Starr