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Design, prototype, implement and optimize predictive models for sporting outcomes. Collaborate in an agile, multidisciplinary team, apply probability and machine learning methods, deploy models, and mentor junior colleagues.

Lead and manage a team of data scientists to design, build and deploy predictive sports models. Oversee algorithm development (probability, Monte Carlo, ML), mentor staff, collaborate with engineers and product managers, and ensure continuous delivery and high-performance, production-ready model implementations across multiple sports.

Develop and implement predictive models for sporting outcomes. Prototype, evaluate, optimize algorithms (Monte Carlo, neural nets, regressions, ensembles). Collaborate in an Agile, cross-functional squad and support model deployment and retraining.

The role involves designing and operating real-time AI systems for sports analysis, integrating various data signals under tight constraints and mentoring other engineers.