The Data Product Analyst serves as a critical bridge between business stakeholders, analytics teams, and data management groups.
This role combines strong data analysis capabilities with core business analysis skills to ensure that data is effectively leveraged to inform strategic decision making, improve processes, and influence solution design.
In addition to championing data stewardship, the Data Product Analyst plays a key role in eliciting requirements, documenting business processes, and facilitating alignment across technical and business teams.
Requirements
Bachelor's degree in information systems, business analysis, or related fields.
2–5 years of experience in data analysis, business analysis, product analytics, or similar roles.
Proven ability to work effectively in cross‑functional environments and support the delivery of data products that serve multiple stakeholders.
Skilled at requirements elicitation, process mapping, and translating business needs into technical specifications.
Skilled in crafting user stories, acceptance criteria, and high‑quality product and data documentation to support scalable, repeatable workflows.
Strong understanding of data stewardship principles, including data quality, lineage, metadata management, and responsible data use and the ability to adapt analytical and stewardship skills across a wide range of client use cases.
Comfortable connecting data across multiple client systems and enriching datasets to enable new insights for sports, fan, and business stakeholders.
Excellent communication, with the ability to tailor messages for both technical teams (engineering, data science) and business stakeholders (club personnel, league departments).
Champions a consumer-first mindset, consistently grounding product, data and insights decisions with a deep understanding of consumer behaviors and needs.
Collaborative mindset with the ability to influence without authority and drive alignment across cross‑functional teams.
Strong analytical toolkit leveraging SQL, Python, and data querying tools to explore, transform, and validate complex datasets that span across multiple product disciplines.