Data & AI Product Manager
About this role
Employer-provided description, formatted for easier reading.
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.
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
Data & AI Product Strategy
- 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.
End-to-End Product Ownership
- 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.
AI-Powered Insights & Foresight
- 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.
Business Partnership & Cross-Functional Product Delivery
- 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.
Adoption, Value & Product Performance
- Define product success measures spanning adoption, engagement, data quality, reliability, efficiency, user experience, decision impact, and measurable business value.
- Drive adoption through stakeholder engagement, enablement, change management, documentation, and continuous product improvement.
- Ensure product investments are connected to measurable business outcomes rather than delivery milestones alone.
Qualifications
- 6+ years of experience across data/analytics product management, digital product management, analytics, data strategy, or related roles, including experience owning complex enterprise products.
- 3+ years of direct product management experience preferred, including responsibility for product strategy, roadmap, prioritization, requirements, delivery, and adoption.
- Demonstrated experience building or managing enterprise data, analytics, business intelligence, or AI-enabled products.
- Strong understanding of modern data and analytics ecosystems, including SQL, cloud data platforms, data pipelines, semantic/data models, APIs, BI platforms, and AI/ML capabilities.
- Technical familiarity with GCP, Databricks, SQL, and Python strongly preferred.
- Experience with Looker, Power BI, or comparable business intelligence and analytics platforms preferred.
- Experience with GenAI, conversational analytics, AI agents, automated insights, or AI-enabled enterprise products strongly preferred.
- Strong understanding of data quality, governance, metadata, security, privacy, and responsible AI considerations within enterprise environments.
- Demonstrated ability to translate ambiguous business problems and executive decision needs into clear product strategies and scalable technical capabilities.
- Strong product judgment with the ability to prioritize across competing business needs, technical constraints, user experience, and long-term scalability.
- Experience operating across global, cross-functional, and highly matrixed organizations.
- Strong stakeholder management and executive communication skills, with the ability to influence without direct authority.
- Highly analytical and comfortable defining and using product metrics to evaluate adoption, performance, and business value.
- Strong written and verbal communication skills with the ability to communicate effectively across business, technical, and executive audiences.
- Collaborative, curious, resourceful, and comfortable operating in an evolving environment where not all requirements or solutions are known upfront.