Senior Quantitative Analyst

The Senior Quantitative Analyst owns mathematical models for pricing sportsbook markets and managing risk. They develop pre-match and in-play pricing models, set margin frameworks, and mentor junior quants. The role requires 5+ years of quantitative analysis experience with 3+ in sports betting, expert Python and SQL skills, and machine learning knowledge.

• Own the design, development, and calibration of pre-match and in-play pricing models, BetBuilder models, and Cashout for assigned sports verticals.
• 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.

• 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.