Sr. Director, Data Science & AI, Orthopedics

Johnson & Johnson announced plans to separate our Orthopedics business to establish a standalone orthopedics company, operating as DePuy Synthes. The process of the planned separation is anticipated to be completed within 18 to 24 months, subject to legal requirements, including consultation with works councils and other employee representative bodies, as may be required, regulatory approvals and other customary conditions and approvals. Should you accept this position, it is anticipated that, following conclusion of the transaction, you would be an employee of DePuy Synthes and your employment would be governed by DePuy Synthes employment processes, programs, policies, and benefit plans. In that case, details of any planned changes would be provided to you by DePuy Synthes at an appropriate time and subject to any necessary consultation processes. 

Job Overview 

The Sr. Director, Data Science & AI provides strategic and operational leadership for enterprise‑wide data science and artificial intelligence capabilities supporting DePuy Synthes. Reporting to the Chief Data and AI officer this role will shape and lead the enterprise Data Science and AI organization; defining the strategy, standing up the AI Hub, setting the technical standards and building the team that delivers AI at scale across R&D , Supply Chain, Manufacturing, Quality, Commercial and Corporate functions.  

The successful candidate is a hands on technologist and strategist in equal measure; able to lay out a multi-year AI strategy for executive audience, evaluate architecture and models, establish governance and standards the make AI safe and defensible in a regulated MedTech environment and lead delivery through global operating model in close proximity with  global capability center(GCC). 

Key Responsibilities 

• Define and lead the enterprise Data Science & AI strategy, roadmap and investment in alignment with business priorities and IT objectives, spanning machine learning,generative AI and agentic AI. 

• Build, lead, and develop high‑performing Data Science and AI team. Hire top talent define roles and career paths and establish a culture of rigor, speed and accountability.  

• Serve as a senior Technical voice for AI across the enterprise, translating business problems into AI opportunities and setting realistic expectations grounding into what technology can and cannot do. 

• Stand up and operate the enterprise AI hub; Shared platform, reusable patterns. Model registry and delivery accelerators through which all AI use cases are built and deployed. 

• Establish standards and reference architectures for generative and agentic AI, orchestration frameworks, retrieval patterns, semantic layers/knowledge graphs, agent action boundaries, observability and Human in the loop controls. 

• Evaluate and manage the AI tech stack and vendor ecosystem ( cloud ML platforms, GenAI Providers, data science tooling) including build vs buy decisions and commercial negotiations in partnership with procurement. 

• Partner with business and functional leaders to identify, prioritize, and deliver high‑value analytics and AI use cases. 

• Design and operationalize the enterprise AI governance framework; Model risk management, validation standards, explainability, bias and fairness testing, drift monitoring and audit trails. 

• Partner with Quality, Regulatory, legal and privacy to ensure AI deployments meet GxP,21 CFR Part 11, SOX and data privacy obligations. 

• Track and evaluate emerging AI capabilities( frontier models, Agentic frameworks, domain specific models) and bring the right one into enterprise. 

• Oversee the design, development, and deployment of scalable data science and AI solutions, including predictive and prescriptive analytics. 

• Establish governance, standards, and best practices for data science, AI model development, validation, and lifecycle management. 

• Collaborate with enterprise data, digital, and IT teams to enable modern data platforms and advanced analytics capabilities. 

• Track performance, value realization, and adoption of Data & AI initiatives, continuously driving improvement and innovation. 

Qualifications 

Education: 

• Bachelor’s degree required in Data Science, Computer Science, Engineering, Mathematics, Statistics, or a related field. 

• Master’s degree or PhD preferred. 

Experience and Skills: 

Required: 

• 12-14 years of relevant work experience, including senior leadership experience in data science, advanced analytics, or AI. 

• Deep current expertise in AI/ML Landscape; classic ML, Deep Learning, generative AI/LLMs and agentic architectures. 

• Demonstrated expertise in MLOps/LLMOps and production AI at enterprise scale. 

• Working fluency with the modern AI/data stack;eg-Databricks/Snowflake/Sagemaker or comparable platforms, vector database orchestration frameworks and GenAI provider ecosystem( Anthropic, openAI,etc.) 

• Demonstrated ability to translate complex data insights into actionable business outcomes. 

• Experience partnering with senior executives and cross‑functional stakeholders. Executive level communication, able to set strategy with C-suite audiences, defend technical position and rigor and translate between business and deep technical stakeholders. 

• Strong people leadership, talent development, and change management capabilities. 

Preferred: 

• Experience in healthcare, medical technology, life sciences, or regulated industries. 

• Familiarity with enterprise data platforms, cloud‑based analytics, and AI toolsets. 

• Experience establishing AI governance, ethics frameworks, and model risk management. 

• Global or matrixed orga