Why this role exists:

The role exists to own the mathematical models that price sportsbook markets and manage the book's risk exposure. The Senior Quantitative Analyst sits at the intersection of statistical modelling, sports domain expertise, and commercial trading judgement to build and calibrate pre-match and in-play pricing models, set margin and liability frameworks, and turn betting and market data into a measurable pricing edge. At the senior/lead level, the scope includes setting the modelling direction for assigned sports verticals, defining model quality metrics, acting as a technical authority, and mentoring mid-level and junior quants.

What you’ll drive:

• Own the design, development, and calibration of pre-match and in-play pricing models, BetBuilder models, and Cashout for assigned sports verticals (e.g. football, tennis, basketball, esports).
• Derive full market trees from core model outputs — match odds, handicaps, totals, correlated derivatives, player props, and same-game multiples — with internally consistent probabilities.
• Model live scenarios where state changes matter: in-play score, time decay, red cards, momentum, injury and substitution effects, service games, possession-based simulation.

• Extract fair probabilities from competitor and exchange prices (margin removal / de-vigging) and blend market-implied signals with in-house model output.
• Define and maintain liability limits, exposure thresholds, and automated risk-mitigation rules across markets and events.
• Run Monte Carlo simulation of book outcomes to quantify tail risk on major events and accumulator/multiples exposure.
• Support the trading floor during high-liability events with real-time analysis and price recommendations.

• Set the quantitative roadmap for assigned verticals in partnership with Trading and Product leadership.
• Partner with Engineering to productionise models into low-latency pricing services, and define monitoring and alerting requirements.

What makes you a GR8 fit:

Must-have

• 5+ years of quantitative analysis experience, including 3+ years in sports betting, betting exchange, or sports trading/analytics.
• Expert-level probabilistic and statistical modelling skills.
• Expert Python skills for modelling and production code.
• Strong experience in sports-specific model design, including ratings, simulations, and in-play models.
• Experience with both pre-match and in-play pricing.
• Advanced knowledge of bookmaking economics, margin strategy, risk, liability, and exposure management.
• Advanced SQL and experience handling large-scale datasets.
• Experience developing, validating, and deploying models into production with measurable commercial impact.
• Machine learning knowledge and understanding of low-latency/streaming systems.
• English proficiency at B2+ level.