Director, Translational Data Enablement; m​/f​/d

Director, Translational Data Enablement (m/f/d) About Astra Zeneca

AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialization of prescription medicines for some of the world's most serious diseases. But we're more than one of the world's leading pharmaceutical companies.

Welcome to Computational Pathology Munich, one of over 400 sites here at AstraZeneca, providing a collaborative environment where everyone can feel comfortable to be themselves - a value that is at the core of AstraZeneca's priorities. To help you maintain your best self, here's a sneak peek into some of the things we provide: after-work events, lunch & learns, a spacious and sustainable office working environment, events, family and childcare support and of course the Alps around the corner for hiking, biking and skiing.

We'rebuilding a connected, end-to-end Enterprise AIengine - uniting data foundations, AI technology, process reinvention, and business-facing AI to accelerate results across the whole value chain.

Success depends on being exceptional connectors:you'llactivelyleverageexisting capabilities, celebrate and promote reuse, export breakthrough ideas across geographies and functions, and obsess over scaling impact rather than building in isolation. If you thrive in high-collaboration environments where your role is to turn complex, cross-functional problems into reusable, enterprise-wide capabilities - and where the measure of success is adoption and scale, not just innovation - you'll have the platform (and sponsorship) to make it real.

Own the transformation of translational and biomarker data into AI-ready, standardized data products that accelerate drug discovery and development.

The role sits at the critical intersection of science teams (who generate and use the data), technology teams (who build platforms and automation), and peer data leadership across clinical trial submission and preclinical/discovery domains. Primary mandate: deliver high-quality, reusable data products while building capabilities to enableaAI ready and FAIR end to end data flow.

Lead a 12–15 person distributed team and coordinate cross-functionally with peer Directors to ensure enterprise-wide data coherence and strategy alignment.

• Own delivery of analysis-ready datasets to science teams, enabling precision medicine, biomarker discovery, and hypothesis validation

• Work with science stakeholders to understand analytics needs and shape data standards accordingly

• Create data catalogs, metadata standards, and usage guidelines;establish feedback mechanisms for continuous improvement

• Define FAIR-compliant standards for translational/biomarker data (omics, imaging, proteomics, etc.). Establish quality frameworks and SLAs aligned to regulatory, AI/ML, and precision medicine use cases

• Build semantic schemas and harmonization layers enabling integration of data from diverse sources (labs, vendors, partners) into reusable, consumable data products

• Define technical requirements for translational data workflows (ingestion, validation, harmonization, delivery APIs)

• Lead automation initiatives to reduce manual curation (e.g., schema-driven harmonization, intelligent quality assurance). Measure efficiency gains

• Ensure integration with enterprise systems (clinical data lakes, AI/ML platforms)

• Pilotnew technologies(agentic AI, ML-driven quality assurance) at scale

• Recruit, mentor, and scale a 12–15 person distributed team of data stewards and engineers responsible for data curation, validation, and delivery

• Partner with other team leads on shared deliveries,leveraging synergies and cont. increasing efficiency

• Define multi-year roadmap for expanding translational/biomarker data standardization across therapeutic areas and partners

• Drive shift from reactive data cleanup to proactive 'Shift Left' data generation

• Present at industry forums; own P&L for translational data operations

• PhD ormaster degree in bioinformatics, biomedical data science, molecular medicine, or related field

• Published research or thought leadership on biomarker standardization, data harmonization, and data product build and delivery with 5+years experience

• Experience with leading a cross functional, global team…