Senior Quantitative Analyst/ Sports Betting Mathematician

Role overview

This senior role owns the mathematical models that price sportsbook markets and manage book risk exposure for a B2B iGaming platform. The position sits at the intersection of statistical modelling, sports domain expertise, and commercial trading judgement, building pre-match and in-play pricing engines that turn betting and market data into a measurable pricing edge.

Responsibilities

- Design, develop, and calibrate pre-match and in-play pricing models, BetBuilder models, and Cashout features for assigned sports verticals such as football, tennis, basketball, and esports - Derive internally consistent market trees covering match odds, handicaps, totals, correlated derivatives, player props, and same-game multiples - Model live state-dependent scenarios including score changes, time decay, red cards, momentum, injuries, substitutions, and service games - Extract fair probabilities from competitor and exchange prices 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 simulations to quantify tail risk on major events and accumulator exposure - Partner with engineering to productionise models into low-latency pricing services and define monitoring and alerting requirements - Set the quantitative roadmap for assigned verticals and mentor mid-level and junior analysts

Requirements

- 5+ years of quantitative analysis experience, including 3+ years in sports betting, betting exchange, or sports trading and analytics - Expert-level probabilistic and statistical modelling skills - Strong Python skills for both modelling and production code - Advanced SQL and experience handling large-scale datasets - Experience designing sports-specific models including ratings, simulations, and in-play systems - Knowledge of bookmaking economics, margin strategy, risk, liability, and exposure management - Track record of developing, validating, and deploying models into production with measurable commercial impact - English proficiency at B2+ level

Nice to have

- Machine learning expertise and familiarity with low-latency or streaming systems

Benefits and work setup

- Annual benefits cafeteria budget covering sports, medical, mental health, home office, and languages - Paid maternity and paternity leave plus a monthly childcare allowance - 20+ vacation days, unlimited sick leave, and emergency time off - Remote-first setup with tech support and coworking compensation - Team events, internal learning courses, and structured growth programs