Data Product Manager - Careers

THE POSITION

Our roster has an opening with your name on it

We are looking for a Product Manager to join our Data Products team within our Technology. This is a key role in a fast-paced environment working with teams and stakeholders across the business to drive the development and enhancement of our Data Science and Machine Learning products. In this role, you’ll drive the evolution and adoption of our ML Platform, including experiment tracking, model lifecycle management, observability, and feature engineering capabilities that enable data scientists to build, deploy, and monitor models  you’re excited by this challenge and want to work within a dynamic company, then we’d love to hear from you.

In addition to the specific responsibilities outlined above, employees may be required to perform other such duties as assigned by the Company. This ensures operational flexibility and allows the Company to meet evolving business needs.

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. Identify and address issues to continuously improve platform efficiency
• Be an enabling force driving through effective and sustainable change guiding the business through the journey
• Play a key role within the PM community here at Fan Duel, sharing your industry best practice and fostering a culture of knowledge sharing and cross-skilling

What we’re looking for in our next teammate

• 3-6 years of experience as a Product Manager, Product Owner, or Data Scientist delivering impactful data products, with a proven track record of successful project delivery and stakeholder satisfaction.
• Experience working with data warehouse and data science technologies, including platforms such as Python, PySpark, Databricks, AWS, and MLflow ensuring efficient data processing and management.
• Proficiency with popular machine learning frameworks and tools, such as Tensor Flow, PyTorch, or scikit-learn, encompassing model development, training, and deployment to support advanced analytics and predictive modeling initiatives.
• Expertise in using Databricks for scalable data engineering and machine learning workflows, leveraging its collaborative environment and optimized Spark clusters for accelerated development and deployment cycles.
• Strong proficiency in SQL for querying and manipulating large datasets, combined with advanced programming skills in Python for data preprocessing, feature engineering, and model development tasks.
• 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…