Quantitative Researcher

Central London (Hybrid) | Permanent, full-time | £100,000-140,000 plus bonus

Working arrangement: Four days per week in the London office and one day working from home.

Our client, a proprietary trading firm and alternative investment manager, is hiring a Quantitative Researcher for its London-based Betting Solutions team. The firm combines quantitative research and fundamental sports expertise to identify inefficiencies and run systematic strategies on major public sports exchanges.

You’ll build predictive models and algorithms that directly drive sports betting and trading performance. This is a sports-focused role with strong relevance to the prediction-market ecosystem through probabilistic modelling, outcome pricing and systematic trading.

What You’ll Do

 

• Prototype, test and deploy stochastic and machine-learning models to predict market and game outcomes across sports betting markets.
• Develop trading strategies and validate performance through statistical backtesting and simulation.
• Work with data scientists and quantitative developers on mid- to high-frequency strategies for public sports exchanges.
• Write efficient, production-quality Python and automate betting operations to improve speed, accuracy and performance.
• Acquire, clean and analyse large datasets; build data pipelines and ETL workflows, identify patterns and improve processes.
• Communicate findings clearly to traders and colleagues, including biweekly strategy-development reports.

What We’re Looking For

 

• PhD in Computer Science, Mathematics or a similar STEM discipline. A PhD is not required if you have 3+ years of relevant experience at one of the following syndicates: Starlizard, Smartodds, Angstrom, Pythia, Paradine, Jabet or Mustard Systems.
• 3+ years of coding experience, with strong Python, Pandas and software design skills.
• Experience building mathematical or machine-learning models, backed by strong statistics, data research, data mining and analysis.
• SQL/NoSQL experience and experience designing ETL workflows.
• Knowledge of cloud computing platforms, preferably AWS.
• Clear communication and the ability to work independently to tight deadlines.

Nice to Have

 

Experience with data science libraries such as scikit-learn, SciPy and TensorFlow.

Salary & Benefits

 

• £100,000+ salary plus bonus scheme.
• 30 days’ holiday, excluding bank holidays.
• Private health, dental and vision insurance.
• Life and accident insurance.

Interview Process

 

1. Brief initial call with the hiring team.
2. Technical test.
3. Technical interview.
4. Final video or face-to-face interview with the CEO.