Scientific Data and Platforms – Data Product Manager

Scientific Data and Platforms – Data Product Manager  

AstraZeneca’s R&D Data Office is an industry-leading enabler of data and AI strategy. The Data Office provides data services, technology, and data products, supported by data and AI policy and governance, to unlock the value of data that drive innovative science.  

The Data Product Manager is based in the Scientific Data Products and Platforms (SDPP) group within the R&D Data Office, which is part of Data Science and AI in AZ R&D. Together with the SDPP Platform Team, the Data Product Manager will advance the SDPP Platform that serves to provide enriched analytics scientific data when and where it is needed. By making the scientific data Findable, Accessible, Interoperable and Reusable (FAIR), the Platform enables researchers to make new correlations, better characterize disease, improve patient stratification, supervise therapeutic response and ultimately accelerate the drug development process.  

The Data Product Manager holds a critical leadership position within the team, tasked with driving the development and execution of a comprehensive data strategy that ensures the compliant and efficient management of scientific data stored on the platform. This role is crucial in bridging the gap between strategic data management and operational excellence, ensuring that all data assets are handled in accordance with stringent compliance standards while extracting maximum value. The incumbent will be responsible for defining and implementing new data solutions, emphasizing a sophisticated understanding of data governance, quality assurance, and metadata management.  

The role requires a leader with a strategic vision who can align data asset and data product planning with organizational goals, ensuring our data not only meet regulatory requirements but also support AstraZeneca's mission of advancing scientific innovation. This involves close collaboration with various team members, including scientists, researchers, and IT specialists, to gather detailed requirements and enable data products that support cutting-edge research and development. By leading product roadmaps and backlogs with a keen focus on compliance, the Data Product Manager will ensure data integrity and reliability are at the forefront of every initiative.  

A meaningful aspect of the Data Product Manager role within the SDPP Team is leading the development and implementation of data management practices to ensure that data assets are effectively led throughout their lifecycle. This responsibility entails designing and operationalizing the SDPP Data Product Lifecycle, which encompasses the processes and tools necessary to maintain and improve the quality, integrity, and utility of data products from inception to reuse.  

The Data Product Manager will effectively engage in strategic projects within the Data Office, providing leadership and direction in establishing high-quality data governance frameworks that align with industry best practices. This will include the development of robust data models and curation rules, enabling seamless data integration and reuse while maintaining the highest standards of data quality.  

This role demands a visionary data leader with a deep understanding of scientific research data needs, data strategy development, compliant data management and. The ability to drive cross-functional collaboration and ensure that data assets are managed to maximize value while ensuring compliance with standards is essential for the success of AstraZeneca’s SDPP initiatives.  

Accountabilities  

• Lead the Development of the SDPP Data Strategy: Formulate and implement a data strategy that ensures data is run in compliance with AstraZeneca’s standards, supporting efficient data utilization to improve value extraction from data assets.  

• New Data Product Identification: See opportunities for new data products that improve data utilization and meet compliance requirements, securing sponsorship and funding to drive these initiatives forward.  

• Data Product Plannin