THE GAME PLAN Everyone on our team has a part to play You will take ownership of data products that deliver key insights into our business and drive future business decisions Lead elicitation of requirements, in the form of user stories & acceptance criteria, prioritizing the product backlog to streamline the execution of program priorities Work closely with cross-functional teams, including data scientists, engineers, and business stakeholders, to ensure our platform aligns with business objectives and delivers advanced machine learning solutions Partner closely with our Data Science and Machine Learning Data Engineering teams to deliver value through data Bring fresh ideas to the table when working to solve business problems, using your commercial understanding to generate innovative solutions Partner with Engineering teams to define solution and approach Create and maintain user guides, technical documentation, and best practices for the Machine Learning platform, including tooling for experiment tracking, model deployment, feature engineering, and observability Monitor platform performance, model accuracy, and data quality. Hands-on experience with MLflow for experiment tracking, model registry, and model lifecycle management, including integration with Unity Catalog for centralized governance and versioning Familiarity with ML observability and monitoring tools (e.g., Fiddler, Evidently AI, or similar platforms) for tracking model performance, detecting data drift, and ensuring model health in production environments Understanding of Infrastructure as Code (IaC) principles and experience with tools such as Terraform for managing ML infrastructure, governance policies, and reproducible deployments Extensive experience with feature stores, facilitating efficient feature management and reuse across machine learning models, enhancing model accuracy and reducing time-to-market for data-driven solutions.