Quantitative Researcher

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

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

Our client is a proprietary trading firm and alternative investment manager focused on quantitative and fundamental sports trading. Its research-led, technology-driven approach applies predictive systems to major public sports exchanges and alternative markets.

Join the London-based Betting Solutions team at the intersection of quantitative research, data science and strategy development. You’ll turn mathematical and ML research into live trading models, production-quality Python and systematic strategies with a direct impact on trading performance.

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.