Data & AI Product Manager

Description

The Data & AI Product Manager, Digital will lead the strategy, development, and evolution of enterprise data, analytics, and AI products that enable faster, more consistent, and forward-looking business decision-making across the organization.

The Data & AI Product Manager, Digital will lead the strategy, development, and evolution of enterprise data, analytics, and AI products that enable faster, more consistent, and forward-looking business decision-making across the organization.

This role will help build foresight capabilities, enterprise insights infrastructure, advanced analytics capabilities, and scalable learning systems that future-proof how the organization understands market performance, consumers, and business opportunities.

A key focus will be transforming complex and fragmented market performance data into scalable, AI-powered business intelligence capabilities
—moving beyond traditional reporting toward automated insights, conversational analytics, intelligent data harmonization, and decision-support experiences.

The role will operate at the intersection of business strategy, data, analytics, AI, engineering, and user experience
, owning products from strategy and discovery through launch, adoption, optimization, and lifecycle management.

Descriptiobn Continued

• Own the multi-year product vision, strategy, roadmap, and prioritization for strategic enterprise data, analytics, and AI products.
• Translate enterprise and Digital priorities into scalable product capabilities that improve how leaders and teams access insights and make decisions.
• Identify opportunities to evolve traditional reporting and analytics into AI-powered intelligence and decision-support products.

• Own the full product lifecycle across discovery, requirements, design, development, testing, launch, adoption, optimization, and transition/decommissioning.
• Translate business needs into clear product requirements, user stories, acceptance criteria, and prioritized product backlogs.
• Make product trade-offs across business value, user experience, technical feasibility, scalability, cost, and time-to-value.
• Partner with engineering and architecture teams to ensure solutions are reliable, scalable, maintainable, and aligned with enterprise technology standards.

• Drive the evolution of product capabilities including AI-enabled experiences, conversational analytics, automated insight generation, anomaly and opportunity detection, intelligent harmonization, and decision support.
• Partner with Data Science, AI, Engineering, and business teams to identify high-value AI use cases and translate them into scalable product capabilities.
• Establish appropriate human-in-the-loop workflows, transparency, validation, and monitoring for AI-generated insights.
• Continuously evaluate emerging data and AI capabilities and determine where they can create meaningful business value.

• Create alignment around product vision, priorities, scope, success measures, and roadmap.
• Serve as the bridge between business users and technical teams, ensuring products solve meaningful business problems rather than simply deliver technical functionality.
• Orchestrate delivery across Product, Data Engineering, Analytics, Data Science/AI, Architecture, UX, business teams, governance functions, and strategic vendors.
• Establish clear ownership, decision rights, dependencies, milestones, and escalation paths across complex enterprise initiatives.
• Manage strategic vendors and partners where required while maintaining clear internal ownership of product strategy and outcomes.

• Define product…