Director, Translational Data Enablement (m/f/d)

AstraZeneca GmbH; München; Vor Ort; EUR 180.000 - 240.000; Vollzeit

Benefits dieser Stelle

Individual development

Trust & appreciation

Munich office

Diversity & inclusion

Zusammenfassung

AstraZeneca GmbH is seeking a Director, Translational Data Enablement in Munich to lead a 12–15 person distributed team delivering high-quality, reusable translational/biomarker data products. You will drive data standardization, FAIR practices, and AI-enabled automation across science and technology stakeholders.

You will partner across clinical and discovery teams to accelerate drug discovery with scalable data platforms and enterprise integration, shaping multi-year roadmaps and ensuring

Qualifikationen

• PhD or master degree in bioinformatics, biomedical data science, molecular medicine, or related field.
• 5+ years of experience in biomarker standardization, data harmonization, and data product build/delivery.
• Experience leading cross-functional, global teams including budget oversight, hiring and onboarding.
• Familiarity with FAIR data principles, semantic interoperability, or data standards (GA4GH, MIAME).
• Track record scaling data governance or data stewardship programs across labs or studies.
• Familiarity with agentic AI, ML, or LLM-driven automation in data/science workflows.
• Familiarity with biomarker platforms (e.g., Guardant Health, Foundation Medicine, Tempus) or research consortia (SEQC/GTEx).

Aufgaben

• Own delivery of analysis-ready datasets to science teams for precision medicine.
• Collaborate with science stakeholders to shape data standards and analytics needs.
• Create data catalogs, metadata standards, and usage guidelines with feedback loops.
• Define FAIR-compliant standards for translational/biomarker data and SLAs.
• Build semantic schemas and harmonization layers for diverse data sources.
• Define requirements for translational data workflows (ingestion, validation, APIs).
• Lead automation initiatives to reduce manual curation and improve efficiency.
• Ensure integration with enterprise systems (clinical data lakes, AI/ML platforms).
• Pilot agentic AI and ML-driven quality assurance at scale.
• Recruit, mentor and scale a 12–15 person distributed team of data stewards/engineers.
• Partner with team leads to drive cross-functional efficiency and synergies.
• Define multi-year roadmaps for data standardization across therapeutic areas.
• Shift left data generation from reactive cleanup to proactive data creation.
• Present at industry forums; oversee translational data operations P&L.

Kenntnisse

Cross-functional leadership

Global team leadership

Budget oversight

Data governance

FAIR data principles

Semantic interoperability

AI/ML automation

Biomarker data standardization

Biomarker platforms knowledge

Data product delivery

Ausbildung

PhD or Master in bioinformatics / biomedical data science / molecular medicine

Jobbeschreibung

Director, Translational Data Enablement (m/f/d)

About AstraZeneca

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.

Site Description - Munich, Germany

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-endEnterprise 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.

Key responsibilities:

Science Enablement & Delivery

• 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;establishfeedback mechanisms for continuous improvement

Standards & Data Product Strategy

• 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

Platform & Technology

• 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

Team Leadership & Cross-Domain Coordination

• 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,leveragingsynergies and cont. increasing efficiency

Strategic Leadership

• 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

Required experience & qualifications:

• 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 including budget oversight, hiring, onboarding

• Experience with FAIR data principles, semantic interoperability, or data standards in research contexts (GA4GH, MIAME, etc.)

• Track recordscaling data governance or data stewardship programs across multiple labs, studies, or organizations

• Familiarity with agentic AI, machine learning, or LLM-driven automation in data/science workflows

• Familiarity with biomarker platform companies (e.g., Guardant Health, Foundation Medicine, Tempus) or research consortia (e.g., NCI's SEQC,GTEx)

Ready to lead the transformation of healthcare through AI? Join us in building the platform that will power the next generation of life-changing medicines and make a meaningful impact on patients' lives worldwide.

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work atpaceand challenge perceptions.That'swhy we work, on average, a minimum of three days per week from the office. But thatdoesn'tmeanwe'renot flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

At AstraZeneca, we are driven by a shared purpose to make a difference in patients' lives through innovation and collaboration. Our dynamic environment encourages continuous learning and growth as we explorenew technologiesand challenge conventional approaches. By partnering across functions andleveragingour data capabilities, we empower our teams to achieve remarkable outcomes. Join us as we shape the future of healthcare and contribute to AstraZeneca's mission of delivering life-changing medicines.

#EAI

Benefits:

• Individual development opportunities with a focus on lifelong learning

• Trust, appreciation, and room to shape things in a focused and passionate team

• Modern office space in Munich enabling collaborative, flexible, and agile work

• A diverse, inclusive, and bias-free work environment, actively welcoming applications from all qualified candidates, regardless of background or characteristics

Date Posted

14-Sept.-2026

Closing Date

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.