We are on a mission to pioneer the world’s next era of play. As we grow across Europe and Latin America, we’re building The Playstack – the technology powering the next generation of sports, gaming, and fan experiences. Join us, and help make it the most widely used platform in the world! From operations, to marketing, to product, we are looking for talented people who will shape how millions of customers play, watch, and connect every day.
In Superbet, the Quant team is responsible for developing the models and tools required for trading a wide range of sports. We aim to provide the best betting experience to our current customers and those we will acquire during our expansion across the globe. This means producing prices for the full range of markets that our customers expect, same-game accumulators, high betting availability, and a great cash out experience.
Junior Sports Quantitative Analyst
As a Junior Sports Quantitative Analyst, you’ll work alongside senior quants, traders, and engineers to help research, build, validate, and deploy models and tooling that power our sportsbook. This is a hands‑on role that combines mathematics, statistics, programming, and product curiosity. You’ll be supported to develop into an independent model owner over time.
What you’ll be doing
- Support the development, testing, and maintenance of mathematical and statistical models for core and derivative markets across multiple sports
- Assist with contingency / correlation modelling required for bet builder and same‑game accumulators
- Collect, clean, and analyse large sports, trading, and market datasets and feeds
- Run backtests, investigate model performance, and help iterate on model parameters and methodology
- Build and improve internal tools that help traders operate efficiently and safely
- Collaborate with engineering to integrate models and analytics into production systems (reliability, performance, observability)
- Document analysis, assumptions, and changes; communicate findings clearly to the team
We are looking for someone who
- Has a strong foundation in probability, statistics, and applied mathematics
- Has solid programming skills in Python (or similar), and is comfortable working with data (pandas / SQL or equivalent)
- Can reason clearly about modelling assumptions, bias, and validation
- Is curious and proactive, with a willingness to learn and take ownership over time
- Communicates technical work clearly
- Has a strong work ethic with a drive for completing high‑quality work
Bonus points if you have
- Exposure to sports analytics or sports betting markets
- Experience working with large datasets and/or real‑time data feeds
- Familiarity with statistical learning / optimisation techniques
- Golang experience
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