[Hiring] Director ISC Data and AI @BD

Role Description

The Director of ISC Data & AI is accountable for establishing and driving the data foundation that underpins the end-to-end Integrated Supply Chain (ISC) Digital Transformation agenda. This role owns data governance, ownership, and stewardship across the supply chain value chain (plan, source, make, deliver), and leads the design and standardization of ISC data models, reusable data products, and a contextualized data ontology that connects supply chain data to business meaning.

The role also owns the standardization, consistency, and central registration of AI agents developed across ISC, ensuring the organization's growing portfolio of AI/agentic capabilities remains governed, auditable, interoperable, and reusable.

The Director will partner closely with ISC functional leaders, TDS/Data Engineering, Enterprise Architecture, Analytics, and Responsible AI teams to ensure data and agents are trusted, discoverable, and AI-ready.

Key Responsibilities

• Data Governance, Ownership & Stewardship
  • Define and operationalize an ISC-wide data governance framework, including policies, standards, roles (data owners, stewards, custodians), and decision rights across all supply chain domains in partnerships with TDS and GBS.
  • Establish a federated data stewardship model, assigning clear accountability for data quality, definitions, and lifecycle management to functional/domain owners across plan, source, make, deliver, and return.
  • Drive data quality management: define KPIs/metrics for completeness, accuracy, timeliness, and consistency; implement monitoring, issue resolution, and continuous improvement processes.
  • Ensure compliance with enterprise data policies, security, privacy, and regulatory requirements as they apply to supply chain data.
  • Chair and actively participate in data governance councils/forums, resolving cross-functional data conflicts and prioritization.
• Data Standardization Across End-to-End ISC
  • Lead the definition and enforcement of common data standards, taxonomies, and master/reference data across all ISC systems and processes.
  • Drive harmonization of disparate data sources into consistent, standardized definitions and formats.
  • Partner with IT and enterprise architecture to retire redundant data structures and reduce fragmentation across legacy systems.
• Data Modeling & Data Products
  • Own the design and evolution of enterprise-grade conceptual, logical, and physical data models representing the end-to-end supply chain.
  • Define and lead delivery of a portfolio of reusable, business-aligned data products that can be consumed across analytics, AI, and operational use cases.
  • Establish data product management practices: intake, prioritization, lifecycle ownership, documentation, and consumption metrics.
  • Ensure data models and products are designed for scalability, reusability, and interoperability across cloud/data platform architecture.
• Data Ontology & Contextualization
  • Develop and maintain a contextualized ISC data ontology/semantic layer that connects raw data to business concepts, relationships, and processes.
  • Enable knowledge graph and semantic capabilities that support advanced analytics, natural-language query, and AI/agentic use cases.
  • Ensure ontology design aligns with industry frameworks/standards where applicable, adapted to organizational context.
• AI Agent Governance, Standards & Registration
  • Define and own the standard for AI agent development across ISC in compliance with BD enterprise standards.
  • Establish and maintain a centralized AI Agent Registry/Catalog for ISC consistent with BD enterprise standards.
  • Require all ISC AI agents to be registered centrally prior to production deployment.
  • Define standard agent-to-data interaction patterns, ensuring agents consume data exclusively through governed data products.
  • Establish consistency standards across agents for naming conventions, logging and observability, and error handling.
  • Define and enforce risk and control tiering for agents including access management.
  • Partner with Enterprise AI/Responsible AI, IT Security, and Legal/Compliance to ensure agent standards align with enterprise AI governance policy.
  • Drive platform interoperability principles so agents built on different platforms can discover, register, and interoperate.
  • Establish a review/certification process that all new ISC agents pass through before production release.
  • Monitor agent performance, drift, redundancy, and retirement throughout the post-deployment lifecycle.
  • Publish and maintain reusable agent design patterns and reference architectures.
• AI & Digital Transformation Enablement
  • Ensure the data foundation is AI-ready — supporting GenAI, predictive/prescriptive analytics, agentic AI, and automation initiatives across ISC.
  • Partner with AI/ML, analytics, and digital transformation teams to identify high-value use cases.
  • Serve as the accountable owner for agent standardization and registration.
  • Act as key advisor to ISC leadership on data, AI, and agent strategy.
  • Track and communicate the value/ROI of data governance, AI-enablement, and agent standardization initiatives to executive stakeholders.
• Leadership & Stakeholder Management
  • Build, lead, and develop a team of data governance, data modeling/architecture, and data product professionals.
  • Serve as the primary liaison between ISC functional leaders, IT/Data Engineering, Enterprise Architecture, Analytics/AI, and external partners.
  • Influence and align senior stakeholders across a matrixed organization without direct authority over all data sources.

Qualifications

• 10+ years of experience in data management, data governance, data architecture, or analytics, with at least 5 years in supply chain, manufacturing, or operations contexts.
• Proven track record leading enterprise data governance programs and data modeling initiatives at scale.
• Experience building or scaling data product organizations is highly valued.
• Experience with data ontology, knowledge graphs, or semantic layer design preferred.
• Experience establishing or governing an AI agent inventory/registry is strongly preferred.
• Exposure to multiple agent/automation platforms with the ability to define platform-agnostic standards.
• Prior experience in a large-scale digital transformation program.

Skills & Knowledge

• Deep understanding of end-to-end supply chain processes and associated data domains.
• Strong knowledge of data governance frameworks, master data management, and data quality practices.
• Working knowledge of data modeling techniques, data architecture, and modern data platforms.
• Familiarity with ontology/semantic technologies and their application to enterprise data.
• Understanding of agentic AI architecture concepts.
• Familiarity with AI risk classification frameworks and responsible AI/model governance practices.
• Ability to define technology-neutral standards that remain enforceable across a heterogeneous, multi-platform agent landscape.
• Strong stakeholder management, influencing, and executive communication skills.
• Ability to translate technical data concepts into business value for non-technical audiences.

Education

• Bachelor's degree in Supply Chain, Data/Computer Science, Information Systems, Engineering, or related field required; Master's degree preferred.
• Relevant certifications in data and AI is a plus.

Benefits

• To find purpose in the possibilities, we need people who can see the bigger picture.
• We welcome people with the imagination and drive to help us reinvent the future of healthcare.
• At BD, you’ll discover a culture in which you can learn, grow and thrive.
• We believe that when people connect in person, we learn faster, collaborate more deeply, and build a stronger culture.

Company Description

Becton, Dickinson, and Company is an Equal Opportunity Employer. We evaluate applicants without regard to race, color, religion, age, sex, creed, national origin, ancestry, citizenship status, marital or domestic or civil union status, familial status, affectional or sexual orientation, gender identity or expression, genetics, disability, military eligibility or veteran status, and other legally protected characteristics.