Position OverviewThe Applied Machine Learning Lead is a senior, hands-on role responsible for ensuring Data Science and Machine Learning initiatives deliver measurable business value. The role combines product ownership, roadmap management, advanced analytics, production-ready machine learning engineering, experimentation ownership, technical standards, and deep iGaming expertise. The focus is on identifying high-value opportunities, prioritising initiatives, delivering robust and scalable data science solutions, evaluating outcomes, and driving adoption of data-driven decision-making across the business.Success in this role is measured not only by model performance, but by the impact those models have on player behaviour, commercial outcomes, product performance, and the ability of the Data Science function to deliver reliable, reusable, and scalable solutions.Key ResponsibilitiesLead and perform advanced commercial and business-focused analyses to support strategic decision-making.Design, build, deploy, and maintain production-grade statistical and machine learning models, applying software engineering best practices to improve maintainability, reliability, testing, observability, and speed from experimentation to production.Own the end-to-end experimentation lifecycle, from hypothesis definition and experiment design through implementation, validation, analysis, interpretation, and iterative optimisation.Ensure analytical recommendations and model outcomes are grounded in statistically sound methods and commercially meaningful results.Review, validate, and challenge analytical work, experiments, and machine learning models to ensure technical correctness, robustness, scalability, and business relevance.Own and manage the data science backlog and roadmap, prioritising…