Director, Data Intelligence Global Development

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com . As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit. Job Function: Data Analytics & Computational Sciences Job Sub Function: Data Science Job Category: People Leader All Job Posting Locations: Madrid, Spain Job Description: Johnson & Johnson Innovative Medicine R&D DDSAI are recruiting for a Director, Data Intelligence - Global Development . Locations: Madrid or Hyderabad J&J Innovative Medicine develops treatments that improve the health of people worldwide. Research and development areas encompass oncology, immunology, neuroscience, cardiopulmonary and specialty ophthalmology. Our goal is to help people live longer, healthier lives. We have produced and marketed many first-in-class prescription medications and are poised to serve the broad needs of the healthcare market – from patients to practitioners and from clinics to hospitals. To learn more about Johnson & Johnson Innovative Medicine visit https://innovativemedicine.jnj.com/ The Director, Data Intelligence - Global Development leads a new capability that turns trusted, AI-ready data products into reusable intelligence for human and AI-assisted decision-making. The role is responsible for analytical enrichment, decision intelligence and agent enablement across Global Development, with an emphasis on building once and reusing across studies, programs and operational domains. This leader heads a team of Decision Scientists and works closely with Data Strategy, Data Products, AI & Data Science, Program & Product Management and Global Development business leaders. A critical partnership is with JJT (IT): Data Intelligence defines the business logic, decision frameworks, intelligence specifications, acceptance criteria and value measures, while JJT (IT) leads production engineering, platform integration, security, deployment, scaling and operations. Key Responsibilities Capability Strategy and Leadership Define and evolve the Global Development Data Intelligence strategy and capability roadmap, aligned with the GD data strategy, data product roadmap and enterprise AI direction. Lead, coach and develop a team of Decision Scientists working across analytical enrichment, decision intelligence and agent enablement. Identify intelligence needs that recur across initiatives and translate them into reusable capabilities within data products. Set priorities and success measures for the capability, and provide evidence of adoption, reuse and value to Global Development leadership. Reusable Analytical Enrichment Lead the definition of reusable descriptive, predictive and prescriptive intelligence capabilities embedded in data products. Translate business questions into intelligence requirements, decision criteria, quality expectations and acceptance tests. Partner with AI & Data Science on model-based capabilities; AI & Data Science develops and validates models, while Data Intelligence defines the operational need and integrates validated outputs into data products. Ensure intelligence capabilities are reusable across decisions, studies and programs rather than recreated as isolated outputs. Decision Intelligence and Knowledge Activation Establish approaches for capturing and operationalizing decision context, process knowledge, assumptions, constraints, trade-offs and rationale. Partner with Data Products, which owns the semantic and knowledge layer, to ensure decision knowledge is modeled, governed and reusable. Create decision frameworks that improve consistency, transparency and continuity across Global Development. Promote responsible, explainable use of decision intelligence, including human review and escalation where appropriate. Agent Enablement Define the business context and decision logic that AI assistants and agents need, building on AI-ready data products. Partner with AI & Data Science on AI and GenAI methods and with the Head of GenAI on standards and governance. Define the decision fitness, acceptance criteria and value measures for agent-enabled use cases. Ensure business context and intelligence specifications are designed for safe, explainable and reusable consumption. Partnership with JJT (IT) Engage JJT (IT) from the outset to align intelligence requirements with reusable services, enterprise architecture, security and operational constraints. Provide business logic, intelligence specifications, decision frameworks, quality expectations and acceptance criteria to JJT (IT). Partner through build, test, deployment and improvement; JJT (IT) leads production engineering, platform integration, security, scaling, support and technical operations. Jointly monitor production quality and performance, with Data Intelligence accountable for decision relevance and JJT (IT) accountable for technical reliability and operations. Cross-Functional Partnership and Value Partner with Program & Product Management, which leads the portfolio and product roadmap, to inform prioritization with intelligence needs and value evidence. Work directly with Global Development experts who own the decision context, adopt the capability and realize the business outcome. Collaborate with Data Strategy on capability direction and value frameworks, and with Data Products on the data product roadmap and knowledge layer. Communicate the Data Intelligence vision, progress, risks and outcomes to senior stakeholders. Qualifications Education and Experience Master's degree or PhD in data science, statistics, operations research, biomedical informatics, computer science, life sciences or a related discipline, or equivalent experience. 8+ years of relevant experience in pharmaceutical or biotechnology R&D, clinical development, advanced analytics, data products, decision science or a related field. Demonstrated experience leading multidisciplinary teams and influencing across business, data science and technology organizations. Track record of translating complex business questions into reusable analytical or decision-support capabilities in a regulated environment.