ConvergeSPORTS - Technical Product Manager - Analytics & Insights - Innovation_Delivery_Transformation

Technical Product Manager For Analytics & Insights

The Team ConvergeSPORTS is a product-driven business combining Deloitte's sports industry experience with proprietary data, AI-native decision intelligence, and reusable Converge capabilities. We help sports organizations grow revenue, deepen fan engagement, optimize partnerships, and improve commercial performance while operating with the focus of a product company. The Analytics & Insights product suite turns sports, fan, sponsorship, partnership, audience, and commercial data into reusable decision capabilities. Its products combine governed data, analytical models, and intuitive workflows to help sports organizations identify opportunities, prioritize actions, and measure commercial outcomes. The Product Management team defines how these technical capabilities become scalable products. It works across Data Science, Data Engineering, Software Engineering, Design, and Go-to-Market to translate market needs into clear product requirements, technical priorities, and repeatable product experiences. Position Summary ConvergeSPORTS is seeking a Technical Product Manager for Analytics & Insights to own the translation between market needs, product strategy, data architecture, analytical capabilities, and engineering execution. You will define technically grounded roadmaps, convert complex data and model requirements into buildable product increments, and ensure new capabilities are reliable, reusable, and commercially relevant. This role is ideal for a product leader who can operate comfortably with engineers and data scientists while maintaining a clear view of user value and product outcomes.

Work you'll do You will manage the technical product lifecycle for Analytics & Insights, from discovery and architecture alignment through backlog execution, launch, adoption, and continuous improvement. Your work will include:

• Define and maintain the product vision, roadmap, success measures, and release priorities for Analytics & Insights capabilities.
• Translate user, buyer, and business needs into technical product requirements, user stories, acceptance criteria, data contracts, API requirements, and workflow specifications.
• Partner with Data Science to define model use cases, output requirements, explainability needs, evaluation criteria, and product integration patterns.
• Partner with Data Engineering and Software Engineering to align roadmap priorities with architecture, platform dependencies, scalability, security, observability, and technical debt.
• Own backlog prioritization and sprint readiness, including story refinement, dependency management, sequencing, and acceptance of completed work.
• Define how data, analytical outputs, recommendations, and AI-assisted features appear within product workflows and support user decision-making.
• Establish measurable launch and adoption criteria, including product usage, reliability, data quality, time to insight, user satisfaction, and commercial impact.
• Lead product discovery, technical design discussions, sprint reviews, release planning, demonstrations, and stakeholder decision forums.
• Balance client and market feedback with reusable architecture, preventing one-off requests from creating fragile or non-scalable product behavior.
• Create product documentation, technical narratives, roadmap materials, release communications, and enablement assets for users, sellers, and delivery teams.

The successful candidate would possess these skills: Strong technical product judgment and the ability to distinguish user needs from implementation choices. Ability to communicate effectively with software engineers, data engineers, data scientists, designers, commercial leaders, and executive stakeholders. Structured prioritization that makes tradeoffs across user value, revenue potential, engineering effort, risk, and platform reuse explicit. Ability to turn ambiguous business questions into precise requirements, workflows, and measurable acceptance criteria. Comfort working with data products, APIs, analytical models, cloud platforms, and production software systems. Curiosity about sports business models, fan behavior, sponsorship, partnerships, and commercial decision-making.

Qualifications Required: Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, Business, Economics, or a related field, or equivalent professional experience. 5+ years of experience in product management, technical product management, software product development, data product management, or technology consulting. 3+ years of experience managing a roadmap and backlog for a software, data, analytics, AI, or platform product. 3+ years of experience writing user stories, technical requirements, acceptance criteria, workflow specifications, API requirements, or data contracts. 2+ years of experience working directly with software engineering, data engineering, or data science teams through an Agile product development lifecycle. Ability to travel up to 15%, on average, based on client and product needs. Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred: Experience launching at least one data-intensive, analytics, AI-enabled, or enterprise software capability into production. Experience using product development tools such as Jira, Confluence, Azure DevOps, Figma, or comparable platforms. 2+ years of experience with sports, media, entertainment, sponsorship, fan engagement, CRM, ticketing, loyalty, or consumer behavior products. Experience defining products that use machine learning, recommendation, scoring, forecasting, optimization, or LLM/agentic capabilities. Experience with SQL, data modeling, REST APIs, cloud data platforms, or software architecture sufficient to support technical product decisions. Experience defining product metrics, instrumentation, adoption reporting, reliability measures, or product operating dashboards. Product management, Agile, cloud, data, or AI certification, or a master's degree in a relevant field.