About Innovative Medicine Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow. Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way. Learn more at Role Summary. The Senior Manager Data Products – Therapeutic Area (TA) is responsible for shaping and delivering high-value, user-centric data products that enable advanced analytics, data science, and AI/ ML capabilities across the Therapeutic Area. This role focuses on translating TA scientific and data science needs into scalable, reusable, and AI-ready data products, spanning preclinical, translational, clinical, competitive intelligence, and real-world data (RWD/ RWE). Working in close partnership with TA Data Science teams, scientific leaders, and the broader Data Strategy & Products organization, this leader ensures that data products are fit-for-purpose, semantically consistent, interoperable, and aligned with enterprise standards, accelerating discovery, evidence generation, and regulatory readiness. Key Responsibilities. Data Product Delivery & Roadmap Execution. Own the delivery of TA-facing data products, translating scientific and analytics use cases into clear functional and technical requirements. Contribute to and execute a TA data product roadmap aligned with enterprise data strategy, spanning discovery, translational research, clinical development, and real-world evidence. Lead or support agile product delivery, ensuring adherence to FAIR data principles (Findable, Accessible, Interoperable, Reusable). Drive integration and harmonization of internal and external data sources, including clinical trial data, omics, imaging, competitor intelligence, registries, and RWE datasets. Ontology, Metadata & Semantic Enablement. Contribute to the development, curation, and application of TA ontologies to ensure semantic consistency across discovery, clinical, regulatory, and real-world data. Align TA semantic models and metadata with enterprise standards and external frameworks (e.g., CDISC, GA 4 GH, FHIR, NCI Thesaurus). Partner with ontology, metadata, and governance teams to ensure data products are AI-ready and semantically enriched. Cross-Functional Collaboration. Partner closely with TA Data Science, clinical, translational, and scientific stakeholders to co-design data products that maximize scientific and analytics value. Collaborate with Data Product Architecture & Governance, Knowledge Management, and Master Data Management teams to ensure seamless integration into enterprise knowledge graphs, catalogs, and platforms. Interface with IT, compliance, and regulatory partners to ensure data products meet quality, privacy, and global regulatory expectations. Team Leadership & Operating Model Support. Provide day-to-day leadership and technical direction to product owners, data engineers, and TA data domain experts. Support the implementation of governance models, agile practices, and delivery standards for TA data products. Act as a coach and mentor, strengthening product, semantic, and data literacy capabilities within the team. Value Realization & Stakeholder Communication. Define and monitor product-level KPIs to assess impact on scientific insights, analytics velocity, trial efficiency, and regulatory outcomes. Communicate progress, outcomes, and value realization to TA leadership, Data Science teams, and broader stakeholders. Actively champion adoption, reuse, and data literacy within the TA community. Strategic Impact. The Senior Manager Data Products – TA plays a critical execution and shaping role in transforming TA data assets into trusted, reusable, AI-ready data products. By embedding semantic rigor, enterprise alignment, and strong partnership with Data Science and scientific teams, this role directly accelerates discovery, improves trial design and execution, and strengthens evidence generation and regulatory readiness positioning TA data as a strategic enabler of patient impact and scientific innovation. Qualifications. Education. PhD or Master’s degree in Informatics, Computer Science, Data Science, Life Sciences, or a related discipline. Experience & Skills 6–10 years of experience in pharma/biotech R&D with a focus on data products, data engineering, analytics platforms, or data science. Demonstrated experience delivering domain-specific data products within a Therapeutic Area or scientific domain. Hands-on experience with multi-modal data, including omics, imaging, translational, clinical trial data, and/or RWD/ RWE. Strong understanding of data product design, data modeling, data integration, and data transformation. Familiarity with research, clinical development, and regulatory data requirements. Working knowledge of metadata management, ontologies, semantic models, and knowledge graphs. Experience aligning with industry and enterprise data standards (e.g., CDISC, GA 4 GH, FHIR). Strong collaboration, communication, and influence skills, with the ability to bridge scientific, technical, and business perspectives. Proven ability to drive adoption and change in a complex, matrixed organization.