Director, Data & AI Products

McKesson•Irving, TX

20h

About The Position

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you. Job Summary - McKesson is an impact-driven Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you. As the Director of Product Management, you will own the product strategy and portfolio roadmap for our data / artificial intelligence offerings within our North American Pharmaceutical Services segment. You’ll drive customer-centric innovation, and partner closely with Engineering, Data/AI, Security, and the Business to deliver differentiated, secure, and scalable products. You combine strategic product leadership with hands-on execution—grounded in market insight, strong technical acumen, and data-driven decision-making. Strategy & Portfolio Leadership Define and socialize the product vision and multi-year roadmap aligned to company OKRs and revenue targets. Build portfolio strategies (core platform, AI/ML, integrations, ecosystems, and expansion plays) that balance growth, retention, and scale. Translate market signals, customer needs, and competitive analysis into clear strategic bets and hypotheses. Product Discovery & Execution Oversee discovery with Design and Engineering—problem framing, JTBD, prototypes, usability testing, and validation. Drive execution through modern Agile practices (Scrum/Kanban), backlog prioritization, and cross-functional alignment. Partner with Engineering on technical feasibility, platform investments, scalability, and reliability. Data-Driven Decisions & Metrics Define product success metrics (adoption, activation, retention, AOP, feature engagement, time-to-value). Establish instrumentation and analytics (e.g., product telemetry, funnels, cohort analysis) to inform prioritization. Go-to-Market & Customer Lifecycle Collaborate with the business on positioning, packaging, pricing, enablement, and launch readiness. Partner with the business to drive onboarding, value realization, renewal, and expansion motions. Engage the business and 3rd parties to shape roadmap and validate product-market fit. Security, Compliance, and Responsible AI Ensure “privacy by design,” secure defaults, and compliance with relevant frameworks (e.g., SOC 2, ISO 27001, GDPR/CCPA). Collaborate with Security, Legal, and Data Governance on risk management, model lifecycle, and AI transparency. Establish standards for model evaluation, data quality, and ethical use of AI.

Requirements

Degree or equivalent experience.
Typically requires 12+ years of professional experience and 4+ years of management experience.
8+ years of experience in in product strategy/management, management consulting, or transformation roles ; and at least 3 years leading cross‑functional initiatives
Deep understanding of healthcare industry; experience with data platforms and AI use‑case enablement
Act as a strategic advisor to business and technology leaders to shape Data & AI strategy, operating model, and investment priorities
Strong interpersonal skills with ability to interact effectively with all levels of staff and external vendors
Establish success measures and insights to evaluate product value realization.
Experience with Agile methodologies and modern product management tools.

Nice To Haves

Ability to balance long-term vision with short-term execution.
Proven track record of delivering successful products in a fast-paced environment.
Strong leadership and team-building capabilities.
Strong attention to detail and excellent organizational skills.
Ability to work well under pressure in a fast-paced environment while meeting established deadlines.
Excellent verbal and written communication skills.

Responsibilities

Define and socialize the product vision and multi-year roadmap aligned to company OKRs and revenue targets.
Build portfolio strategies (core platform, AI/ML, integrations, ecosystems, and expansion plays) that balance growth, retention, and scale.
Translate market signals, customer needs, and competitive analysis into clear strategic bets and hypotheses.
Oversee discovery with Design and Engineering—problem framing, JTBD, prototypes, usability testing, and validation.
Drive execution through modern Agile practices (Scrum/Kanban), backlog prioritization, and cross-functional alignment.
Partner with Engineering on technical feasibility, platform investments, scalability, and reliability.
Define product success metrics (adoption, activation, retention, AOP, feature engagement, time-to-value).
Establish instrumentation and analytics (e.g., product telemetry, funnels, cohort analysis) to inform prioritization.
Collaborate with the business on positioning, packaging, pricing, enablement, and launch readiness.
Partner with the business to drive onboarding, value realization, renewal, and expansion motions.
Engage the business and 3rd parties to shape roadmap and validate product-market fit.
Ensure “privacy by design,” secure defaults, and compliance with relevant frameworks (e.g., SOC 2, ISO 27001, GDPR/CCPA).
Collaborate with Security, Legal, and Data Governance on risk management, model lifecycle, and AI transparency.
Establish standards for model evaluation, data quality, and ethical use of AI.