About Gambit
Established in 2005, Gambit Research develops automated tools to facilitate high-speed trading on sports betting markets. On behalf of our clients, we devise and implement strategies to exploit market inefficiencies, then run them on our high-frequency execution platform. Our system is always trading, and we need to maintain a reliable, low latency service and adapt it to the evolving needs of the company and our clients.
When you join us, you’ll find that we have a very flat hierarchy, and that we place an emphasis on employee freedom. You’ll be encouraged to work on projects that you find interesting, as we believe people are most productive when they’re intellectually stimulated. You don’t need to be interested in sports betting.
You’ll be encouraged to maintain a good work-life balance, and will benefit from flexible working hours, quarterly bonuses, private healthcare, private pension contributions, part-funded sabbaticals after five years of service, excellent holiday allowances, an office chef multiple times per week serving healthy lunches, regular employee outings, opportunities to attend conferences in the UK and abroad, an extensive and expanding technical library, and height-adjustable desks.
We’re very proud of the open, intelligent, and collaborative culture at Gambit, and are always looking to expand our Quantitative Research team. You’ll join our team of exceptional individuals, to pool your diverse experiences, and enhance our existing team. So, if you have an interest in problem solving, want to join a company with a stimulating and development focussed culture, and have a proven ability to learn new skills, then we’d love to hear from you.
Purpose of the Role
You’ll be a member of our Quant Team, designing, analysing and improving our clients’ high frequency strategies for the sports betting markets. You’ll be part of a small team, working in a relaxed environment, and using a range of modern open-source tools like Jupyter, PyTorch and Spark. You’ll be working with terabytes of data, and will be part of a team that can quickly run experiments at scale in the markets, allowing us to test our hypotheses in a live environment.
Responsibilities and Duties
Your day-to-day duties and responsibilities will include, but won’t be limited to:
- developing and improving clients’ high frequency strategies
- modelling sports outcomes
- trying to understand betting market dynamics through data analysis or split-testing
- implementing and backtesting new statistical arbitrage strategies
Skills and Competencies
You’ll need to have:
- A solid statistical grounding in regression, hypothesis testing and basic machine learning concepts
- Some previous programming experience, preferably in a Linux or Unix environment
- A good attention to detail, and the ability to absorb and understand large amounts of information
- Well rounded interpersonal skills, and the ability to build long-lasting professional relationships
- Initiative to get on with projects independently, as well as the skills and communication to work in a productive team
Qualifications and Experience
At a minimum you’ll need to be educated to at least degree level (or have equivalent experience), in a numerate subject such as maths, physics or statistics, and demonstrate experience with and enthusiasm for programming and data analytics.
Further advantages would include any of the following:
- Post-graduate qualifications or research in a related field
- Experience, either in academia or industry, in modern machine learning methods: e.g. deep learning, Bayesian methods, graphical models.
- An interest in algorithmic trading strategies and markets
Interested?
Email us your CV, and tell us a bit about you.