Sr Director, Product Management - Data & AI

Sr Director, Product Management
- Data & AI

Hybrid
- Philadelphia, PA 19106

Apr 17, 2026

Pay information not provided

The Sr. Director of Product Management for Data & AI is accountable for defining and driving the enterprise product strategy, roadmap, and value realization for data, analytics, and business intelligence capabilities across the retail organization.

This role owns the product vision and lifecycle for the company’s core data and analytics platforms, including Master Data Management (MDM), Enterprise Data Platform (EDP), and Customer Data Platform (CDP). The Sr. Director ensures these platforms and the analytics and reporting products built on top of them are aligned to business outcomes, delivering measurable impact across merchandising, supply chain, stores, e-commerce, finance, marketing, and customer experience.

This leader partners closely with Engineering, Enterprise Architecture, AI, and business leaders to translate strategy into scalable, high-quality solutions while balancing strategic vision with disciplined execution. This role is also accountable for defining and driving the enterprise AI product strategy across data, analytics, and business platforms—ensuring AI capabilities are purpose-built, value-driven, responsibly governed, and scaled across the enterprise.

Responsibilities include ownership of AI use case strategy, multi-year AI roadmaps, and continuous value realization in partnership with business, technology, and data science leaders.

Define and own the enterprise product vision, multi-year roadmap, and investment strategy for Data, Analytics & BI, aligned to enterprise priorities and retail growth objectives.

Translate business strategies into clear data and analytics products, outcomes, and success metrics across MDM, EDP, CDP, analytics, and reporting.

Partner with executive leadership to inform investment decisions, funding models, and roadmap sequencing based on value, capacity, and dependencies.

Own the end-to-end product lifecycle for MDM, EDP, and CDP.

Work cross-functionally with Data Science, AI/ML, Enterprise Architecture, Infrastructure, Security, and Operations to transition AI solutions from experimentation to reliable, scalable, and supportable enterprise products.

Prioritize capabilities that enable trusted data, self-service analytics, AI enablement, and operational insights.

Lead build vs. buy decisions, vendor evaluations, and roadmap tradeoffs with a long-term value and total cost of ownership lens.

Define and own the enterprise AI product strategy across data, analytics, and business domains, aligned to enterprise priorities and platform capabilities.

Develop and maintain a multi-year AI roadmap, balancing near-term value delivery with long-term platform and capability maturation.

Continuously identify, assess, and shape AI opportunities across the business, translating operational pain points and processes into high-impact AI use cases.

Partner with business leaders and domain Product Managers to deeply understand workflows, decisions, and constraints that could benefit from AI-driven automation, augmentation, or optimization.

Establish clear AI value hypotheses, success metrics, and outcome tracking for each use case (e.g., productivity, cost savings, revenue lift, risk reduction).

Shape and prioritize analytics, reporting, and BI products that deliver actionable insights across merchandising, supply chain, stores, digital, finance, marketing, and customer experience.

Own the enterprise BI strategy, including KPI frameworks, semantic models, dashboard standards, and self-service enablement.

Drive adoption, trust, and usability across analytics and BI platforms by balancing speed, consistency, performance, and governance.

Partner with Data Science and AI teams to enable predictive, prescriptive, and AI-driven use cases, transitioning successful experimentation into enterprise-grade solutions.

Establish and operate clear intake, governance,…