Director, Commercial Data & AI Product Management

Commercial Director, Data & AI Product Management

BD is one of the largest global medical technology companies in the world. Advancing the world of health is our Purpose, and it's no small feat. It takes the imagination and passion of all of us—from design and engineering to the manufacturing and marketing of our billions of MedTech products per year—to look at the impossible and find transformative solutions that turn dreams into possibilities.

We believe that the human element, across our global teams, is what allows us to continually evolve. Join us and discover an environment in which you'll be supported to learn, grow and become your best self. Become a maker of possible with us.

We are seeking a strategic, data-savvy, and AI-forward leader to serve as Commercial Director, Data & AI Product Management—responsible for shaping the commercial data, insights, and AI product strategy across the full commercial ecosystem, from marketing and demand generation through pricing, sales operations, and CRM to service, repairs, and installed-base management.

This role will define and own the product vision, roadmap, and lifecycle for commercial data products, insights platforms, and AI/GenAI-powered solutions. Critically, this role partners with a shared Data, Insights & AI product delivery organization to build, deploy, and manage these products—meaning this role is the strategic product management authority (the "what" and "why") while partnering with the delivery organization on the "how" and "when."

This person is a peer to the three Senior leaders and collaborates closely with all three to ensure data, insights, and AI capabilities are embedded across every layer of the commercial technology ecosystem:

• Director, Global CRM, Sales Operations & Revenue Technology—embedding data, insights, and AI into CRM, CPQ, CLM, Sales Planning, and ICM platforms
• Associate Director, Enterprise Architecture—ensuring data products and AI capabilities align with the target-state commercial architecture, integration patterns, and data governance standards
• Senior Director, Marketing, Service & Repairs Technology—embedding insights and AI into MarTech, FSM, repairs, and installed-base platforms

This leader will bring deep product management expertise in data, analytics, and AI—combined with strong commercial acumen and the ability to translate complex data and AI capabilities into measurable business outcomes that drive revenue growth, operational efficiency, and customer experience improvement across a global MedTech organization.

Responsibilities:

Commercial Data Strategy & Product Vision

• Define the multi-year commercial data product strategy and roadmap spanning marketing, sales, service, and repairs data domains.
• Own the product vision for commercial data assets—including curated data products, master data services, customer 360 views, product/installed-base data, and commercial performance datasets.
• Define data product standards (SLAs, quality metrics, discoverability, self-service) in partnership with Enterprise Architecture.
• Champion a product-based data operating model—treating data as a managed product with clear ownership, consumers, quality SLAs, and lifecycle management.

Insights Products & Commercial Analytics

• Define and own the product roadmap for commercial insights platforms—AI enabled dashboards, self-service analytics, embedded analytics, and decision-support tools across sales, marketing, and service.
• Translate business needs into insights product requirements—including sales performance analytics, pipeline/forecast insights, marketing attribution, service KPIs, pricing analytics, and installed-base intelligence.
• Define KPIs and success metrics for insights products—measuring adoption, business impact, and decision-making improvement.
• Partner with Commercial, Finance, and Business Unit leadership to prioritize insights investments aligned to strategic priorities.

AI & GenAI Product Management

• Define and own the AI/GenAI product strategy for the commercial ecosystem—including intelligent pricing, guided selling, predictive lead scoring, AI-assisted service triage, generative AI for content/proposals, agentic AI for workflow automation, and conversational AI.
• Own the full AI product lifecycle—from opportunity identification and business case development through MVP, pilot, scale, and ongoing optimization.
• Establish AI product governance frameworks—including responsible AI principles, bias monitoring, explainability standards, human-in-the-loop requirements, and compliance with healthcare/MedTech regulations.
• Horizon-scan emerging AI technologies (LLMs, multi-agent systems, autonomous agents) and evaluate commercial applicability.
• Define and track AI product value realization metrics—measuring ROI, adoption, productivity gains, and commercial impact.

Partnership with Shared Delivery Organization

• Serve as the primary product management partner to the shared Data, Insights & AI product delivery organization—providing clear product vision, prioritized backlogs, acceptance criteria, and business context.
• Operate as the strategic "demand side"—articulating the "what" and "why" while the delivery organization owns the "how" and "when."
• Establish joint operating rhythms (sprint reviews, roadmap planning, quarterly business reviews) with the delivery organization to ensure alignment, velocity, and value delivery.
• Co-own product lifecycle governance—including intake, prioritization, release planning, and retirement of data, insights, and AI products.

Cross-Ecosystem Collaboration

• Partner with Director, Global CRM, Sales Operations & Revenue Technology to embed data, insights, and AI into CRM, CPQ, CLM, ICM, and Sales Planning platforms.
• Partner with Sr. Director, Marketing, Service & Repairs Technology to embed insights and AI into MarTech, FSM, repairs, and installed-base platforms.
• Partner with Associate Director, Enterprise Architecture to ensure data products, insights, and AI capabilities align with the target-state commercial architecture, integration patterns, and data governance standards.
• Serve as the commercial voice to enterprise-wide Data & AI governance forums.

Stakeholder Leadership & Change Management

• Serve as the executive-facing owner of the commercial data, insights, and AI product portfolio—presenting strategy, progress, and value realization to senior leadership.
• Drive data literacy, AI fluency, and insights adoption across commercial teams—fostering a culture of data-driven decision-making.
• Lead change management for new AI capabilities—ensuring trust, adoption, and responsible use across the organization.

Required Qualifications:

• 12+ years of progressive experience in data product management, analytics product management, AI/ML product management, or data strategy—with at least 4 years in a leadership role.
• Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Business, or related field; advanced degree (MBA, MS, PhD) preferred.
• Demonstrated experience defining and managing data products, insights platforms, and/or AI products in large, complex organizations.
• Strong understanding of modern data architectures—data lakes/lakehouses, data mesh, data products, CDPs, and analytics platforms (e.g., Snowflake, Databricks, Azure Synapse, Power BI, Tableau).
• Experience with AI/ML product management—including understanding of LLMs, GenAI, NLP, predictive models, and responsible AI frameworks.
• Proven ability to operate in a product management capacity separate from delivery—defining strategy, vision, and priorities while partnering with engineering/delivery teams on execution.
• Experience with Agile product management methodologies and operating as a strategic Product Owner.
• Strong understanding of commercial operations—including sales, marketing, pricing, service, and CRM processes.
• Medical device, MedTech, life sciences, or regulated industry experience required.
• Experience in leading and applying lean and kaizen excellence principles and techniques such as PSP and 5-Whys in achieving commercial objectives of driving growth, productivity, margin expansion and improved customer engagement.

Preferred Qualifications

• Experience with agentic AI, multi-agent orchestration, and autonomous AI systems in commercial contexts.
• Familiarity with data governance frameworks (DMBOK, DCAM) and data quality management practices.
• Experience with customer data platforms (CDPs) and identity resolution in B2B/B2B2C environments.
• Knowledge of responsible AI and ethics frameworks—including bias detection, explainability (XAI), and compliance with healthcare-specific AI regulations.
• Experience building data literacy and AI fluency programs at enterprise scale.
• Familiarity with MLOps, model monitoring, and AI product observability practices