Trader

Harrington Starr; Greater London; On-site; GBP 75,000 - 130,000; Full time

Job summary

Harrington Starr is seeking a Quantitative Sports Trader to cover European and Asian markets, focusing on pre-match and in-play pricing across sportsbooks, exchanges and prediction markets.

You will blend statistical modelling, market analysis and risk management to identify opportunities, manage exposure and improve trading systems for live sports events. The role requires 2–8 years in a sportsbook trading team with strong Python or C# programming skills.

Qualifications

• Experience in sportsbook trading, betting exchanges or sports trading environments.
• Experience pricing or trading sports markets, 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.
• Interest in improving trading processes and systems.

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.

Skills

Quantitative modelling

Statistical analysis

Market analysis

Risk management

In-play trading

Trading strategy

Exposure management

Tools

Python

C#

Job description

Quantitative Sports Trader – European & Asian Markets

Location:

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.