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About the Role

Lead the strategy, development, and evolution of enterprise data, analytics, and AI products to enable faster, more consistent, and forward-looking business decision-making. This role will build foresight capabilities, enterprise insights infrastructure, advanced analytics, and scalable learning systems to future-proof how the organization understands market performance, consumers, and business opportunities. A key focus is transforming complex data into scalable, AI-powered business intelligence, moving beyond traditional reporting toward automated insights, conversational analytics, intelligent data harmonization, and decision-support experiences. The role operates at the intersection of business strategy, data, analytics, AI, engineering, and user experience, owning products from strategy through lifecycle management.

Responsibilities

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 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.

Requirements

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.
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.

Skills

SQL
Cloud data platforms
Data pipelines
Semantic/data models
APIs
BI platforms
AI/ML capabilities
GCP
Databricks
Python
Looker
Power BI
GenAI
Conversational analytics
AI agents
Automated insights
AI-enabled enterprise products

Experience Level

6+ years of experience
3+ years of direct product management experience