Director, Commercial Data Strategy & Governance

We are the people who give possibilities purpose

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 Med Tech products per year-to look at the impossible and find transformative solutions that turn dreams into possibilities.

Job Description

Commercial Data & AI Platform Strategy

* Own the commercial data and AI platform strategy, ensuring alignment to enterprise architecture standards and commercial analytics needs.

* Define and evolve the reference architecture for commercial data, analytics, and AI (including lakehouse patterns, MDM, APIs, and integration standards).

* Establish a scalable, cost‑effective platform foundation that supports analytics, experimentation, and AI at global enterprise scale.

* Partner with IT/GBS to align on shared infrastructure, tooling strategy, and long‑term platform roadmaps.

Future of AI, Industry Foresight & Strategic Enablement

This role is responsible for ensuring the commercial data and AI foundation remains forward‑looking and adaptable as technology, economic conditions, and regulation evolve.

* Maintain deep awareness of emerging AI capabilities, macroeconomic forces, regulatory trends, and technology shifts shaping the future of commercial execution in Med Tech and Life Sciences.

* Evaluate novel AI and GenAI use cases (e.g., agentic workflows, reasoning models, copilots, simulation, real‑time decisioning) from a platform, governance, and scalability perspective for applicability across commercial domains such as sales productivity, forecasting, pricing, customer engagement, and revenue risk management.

* Translate external AI and market trends into forward‑looking platform, architecture, and governance implications, ensuring the commercial data ecosystem is future‑ready without sacrificing trust, security, or compliance.

* Partner with Commercial Decision Science & AI and Commercial Data Product Strategy to enable rapid experimentation with emerging AI capabilities while establishing guardrails that allow solutions to scale safely into production.

* Advise executive leadership on AI platform readiness, enterprise risk posture, and investment tradeoffs as the commercial AI landscape continues to evolve.

Platform Engineering & Enablement

* Own platform engineering roadmap supporting cloud infrastructure, storage, compute, orchestration, Data Ops, and Master Data Management (MDM) for commercial domains.

* Ensure standardized ingestion, integration, and orchestration patterns across commercial source systems (e.g., CRM, CPQ, ERP, GTM, marketing, service).

* Enable platform capabilities that support analytics engineering, decision science, and GenAI use cases (e.g., feature access, historical backfills, observability).

* Design platform capabilities with a forward‑AI lens, ensuring flexibility to support emerging model types, agentic workflows, and evolving data access and compute patterns.

* Drive platforms that prioritize reliability, scalability, performance, and ease of consumption.

Governance, Trust & Compliance

* Own the commercial data governance framework, including operating model, standards, policies, and enforcement mechanisms.

* Implement metadata management, lineage, cataloging, and data discovery capabilities to ensure transparency, auditability, and reuse.

* Define and operationalize data quality frameworks, including automated validation, monitoring, and remediation.

* Establish and enforce access control, privacy, and compliance controls, ensuring adherence to GDPR, SOX, and other applicable regulatory requirements.

* Partner with IT, GBS, Legal, and Privacy teams to ensure commercial data and AI usage meets enterprise risk and compliance standards.

Data Architecture & Standards

* Define data modeling frameworks, integration patterns, and API standards for commercial data domains.

* Ensure architectural consistency across platforms, analytics layers, and AI workloads.

* Govern enterprise standards for data retention, lifecycle management, and…