Senior Staff Product Manager, FBG Data

Fanatics is building a leading global digital sports platform. As the Senior Staff Data Product Manager, you will own the strategy, prioritization, and delivery of data-centric initiatives across the company, ensuring the right data products are built with measurable business impact.

Responsibilities:

• Define and drive our data product strategy, aligning opportunities to more effectively leverage our data with the company’s objectives
• Translate business challenges into data-driven solutions: data products, ML models, dashboards, or infrastructure investments
• Own and maintain the data product roadmap, prioritizing initiatives across multiple stakeholders while balancing short term vs long term business needs Identify and manage trade-offs between data staffing capacity, cross-team dependencies, and business priorities
• Act as the senior program driver across diverse data roles: staff data engineers, data platform engineers, ML engineers, ML platform engineers, analytics engineers, and data scientists
• Lead cross-functional project management for data initiatives, ensuring milestones are met, blockers are cleared, and scope is aligned
• Partner with executive stakeholders to identify opportunities, gather requirements, and report on KPIs for data products
• Represent our data products in executive-level planning and review forums
• Identify and resolve organizational and architectural ambiguity in undefined problem spaces with minimal oversight
• Evangelize data best practices and the value of data-driven decision-making across the org

Requirements:

• 12+ years of experience in product management, program management, or equivalent roles, with at least 8+ years focused on data, ML, or analytics
• Proven track record of shipping data products (e.g., ML-driven features, self-service analytics platforms, reporting suites, or governance tools)
• Deep fluency of data and ML lifecycles from ingestion, modeling, and governance to feature engineering, model training, and deployment
• Hands-on experience partnering with data engineers, ML engineers, and data scientists
• Ability to translate complex data and ML concepts into business value for non-technical stakeholders
• Demonstrated success setting strategy that was later adopted at the executive/board level
• Exceptional skills in roadmap development, prioritization, and cross-functional coordination, including navigating competing or ambiguous priorities across business units
• Strong written and verbal communication skills; comfort presenting to executive leadership
• Experience with ML platforms (feature stores, model registries, inference hosting) or data platforms (lakehouse, governance, catalogs)
• Background in analytics, statistics, or data science and able to independently explore and validate data-driven opportunities