Director Data & Analytics

The Director, Enterprise Data Products & Decision Intelligence Center of Excellence (COE) will define and lead Medline's enterprise approach to building, governing and scaling reusable data products and decision intelligence capabilities. This role provides strategic and operational leadership for the COE, establishing the standards, frameworks, operating model and talent needed to turn enterprise data into trusted, certified products that power analytics, AI and decision‑making tnering closely with business leaders across Supply Chain, Manufacturing, Finance, Sales, Quality, Procurement and other functions, the Director will shape how data is sourced, modeled, productized and activated moving the organization from descriptive reporting toward predictive, prescriptive and AI‑assisted decisions.

Success in this role requires deep techno‑functional fluency, the ability to operate in ambiguity, strong product management discipline, and the leadership to balance immediate business needs with long‑term enterprise data and AI innovation.

Define and own the multi-year vision, strategy and roadmap for enterprise data products and decision intelligence, aligned to enterprise and business unit objectives.

Establish and lead the Data Products & Decision Intelligence COE, including its charter, operating model, engagement model, funding approach and success metrics.

Lead intake, qualification and prioritization of enterprise demand; sequence work against capacity and communicate trade-offs to executive sponsors.

Define business cases, expected benefits and value measures for data product and analytics investments, and report on portfolio progress, adoption and value realization to senior leadership.

Own the enterprise data product portfolio, including product vision, roadmaps, prioritized backlogs and lifecycle management from ideation through deployment and retirement.

Build and scale enterprise data foundations—reusable, governed and certified data products, conformed dimensions and semantic models—that serve multiple business functions.

Establish data product standards, including ownership, SLAs, data contracts, documentation, quality thresholds and certification criteria.

Champion reuse of certified data products over single-purpose solutions; identify and eliminate duplication across business units and functions.

Partner with Data Governance and Information Security on data quality, stewardship, metadata, lineage, access management and compliance requirements.

Lead the evolution from descriptive reporting to diagnostic, predictive and prescriptive analytics that embed insights directly into business decisions and workflows.

Identify and deliver high‑value decision intelligence use cases (e.g., demand sensing, inventory optimization, pricing, margin and cost‑to‑serve analytics, quality and supplier risk) in partnership with business and data science teams.

Enable AI‑ready data, including feature‑ready datasets, semantic layers and governed data for machine learning, generative AI and agentic AI solutions.

Define frameworks for measuring decision outcomes and closing the loop between insights, actions and business results.

Establish COE standards, frameworks, reference architectures, templates and best practices for data products, semantic models, BI and analytics delivery.

Promote data literacy and self‑service analytics through training, communities of practice, workshops and certification programs.

Drive adoption through change management and communication, including retirement of legacy and…