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

AstraZeneca; München; Hybrid; EUR 140,000 - 190,000; Full time

Benefits offered by this job

Individual development opportunities

Modern Munich office

Flexible work environment

Inclusive work culture

Job summary

AstraZeneca in Munich is seeking a senior data leader to transform translational and biomarker data into AI-ready data products. You will lead a 12–15 person distributed team, coordinating with cross-functional Directors to ensure enterprise-wide data coherence and strategy alignment.

Join us to define multi-year roadmaps, drive FAIR data standards, and pilot agentic AI at scale. The role sits at the nexus of science, technology, and data leadership, delivering reusable data assets that

Qualifications

• PhD or master's in bioinformatics, biomedical data science, molecular medicine, or related field.
• 5+ years of experience leading cross-functional, global data teams with budget oversight.
• Strong track record in data governance, FAIR principles and data standards.
• Familiarity with agentic AI, ML automation, and LLM-driven workflows.
• Experience with biomarker data standardization and data product delivery.
• Knowledge of leading biomarker platforms or research consortia is a plus.
• Ability to drive enterprise-level data coherence and strategic alignment.

Responsibilities

• Own the transformation of translational and biomarker data into AI-ready, standardized data products.
• Lead a 12–15 person distributed team and coordinate with peer Directors for enterprise alignment.
• Define multi-year roadmap for expanding translational data standardization across therapeutic areas.
• Define FAIR-compliant standards for translational/biomarker data and establish quality SLAs.
• Pilot new technologies (agentic AI, ML-driven QA) at scale and measure impact.
• Present at industry forums and drive data governance and data stewardship programs.

Skills

Data leadership

Cross-functional leadership

FAIR data principles

Data governance

Biomarker data

Agentic AI

LLM automation

Budget oversight

Education

PhD or MSc

Tools

GA4GH

MIAME

Data standards

Job description

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.

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're building a connected, end-to-end Enterprise AI engine - 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'll actively leverage existing 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 enable a AI 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

• 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

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)
• Pilot new 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, leveraging synergies 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 or master 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 record scaling 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 at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not 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 explore new technologies and challenge conventional approaches. By partnering across functions and leveraging our 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.