Director, Head of CP Delivery Operations (m/f/d)

Director, Head of CP Delivery Operations (m/f/d)

ABOUT ASTRAZENECA

AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialisation 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

At Computational Pathology Munich (CPM), we make a significant contribution to high-performance, data-driven research and development. Our team operates in a demanding, fast-paced environment where excellent collaboration, clear communication and precise organization are critical.

We are seeking a Director of Computational Pathology Delivery Operations (m/f/d) in Munich to lead the execution of Computational Pathology (CP) workflows across AI/ML development, biomarker discovery, and diagnostic readiness in a cross-functional environment. The role is accountable for how CP work is delivered at scale, including people leadership, delivery standards, data and workflow quality, and regulatory readiness.

The ideal candidate brings strong experience in digital pathology operations and data management, along with a practical understanding of clinical development and diagnostic requirements. You will work closely with cross-functional partners to translate requirements into reliable, compliant delivery, while providing direct leadership to CP Delivery Managers.

Key Responsibilities

People Leadership and Matrix Accountability

• Provide direct line management for >10 CP Delivery Managers embedded across drug programs and AI/ML model development initiatives
• Build delivery capability through coaching, role clarity, performance management, and career development
• Establish clear expectations for team member accountability, ownership, and execution quality within a matrixed operating model
• Support Delivery Managers operating in agile, cross-functional teams while maintaining consistent delivery standards
• Partner with Biomarker Development, Computer Vision & AI, Pathology, Data Science, Program Management, Product Management, and Quality Management to improve and scale ways of working, and to establish and maintain effective workflows
• Represent CP Delivery Operations in relevant internal and external forums, including participation in selected industry or data standards (e.g. DICOM, OME, CDISC) working groups where appropriate

Data Management and Governance

• Define and maintain CP data governance both for biomarker discovery and AI-based CP model development, aligned with GLS standards, and bring it towards GxP, GDPR, and diagnostic quality standards, in collaboration with CP Quality Management and Enterprise Data Governance teams
• Establish standards for data models, metadata, and data flow, and ensure team members apply them consistently across programs (FAIR, ALCOA+)
• Ensure CP images, metadata, and annotations produced by teams are suitable for downstream AI/ML development, validation, and regulatory use
• Ensure data practices meet regulatory, quality, and diagnostic development expectations, in collaboration with Quality Management and cross-functional teams,
• Ensure CP Delivery Managers act as the primary user and stakeholder for CP-related data storage platforms and handling tools, providing clear requirements, structured feedback, and acceptance input to product management and software teams to support development and adoption

Workflow Establishment and Execution

• Define, implement and monitor end-to-end CP delivery workflows translating research, clinical, and diagnostic needs into practical execution, in collaboration with Quality Management and cross-functional teams,
• Ensure CP Delivery Managers and embedded teams consistently apply agreed workflows across drug programs and AI-based model development, aligned with CP portfolio priorities and scientific requirements
• Set expectations for execution quality across CP workflows, including documentation, traceability, and audit readiness, and ensure teams meet those expectations
• Ensure teams deliver reliable, standardized CP readouts that support biomarker discovery and program decision-making
• Ensure teams are prepared for inspections and regulatory submissions (e.g. FDA, IVDR) through consistent execution practices and documentation, and that CP delivery outputs are reproducible, traceable, and defensible for scientific review and regulatory scrutiny

Diagnostics & Regulatory Readiness Data Strategy

• Lead data strategy components for diagnostic development, including algorithm validation, reproducibility testing, and post-market data collection
• Drive initiatives to make clinical pathology data analysis-ready for downstream discovery and regulatory use
• Collaborate with Regulatory, Quality, and Clinical Affairs to ensure traceability and compliance of all diagnostic-related datasets
• Support creation of data packages for regulatory submissions and audits

Experience & Qualifications

Essential

• Advanced degree (Ph.D. or M.S.) in a relevant field such as computational biology, biomedical data science, bioinformatics, or a related discipline
• 8+ years of experience in computational pathology, biomedical imaging, or data-intensive scientific environments, ideally within pharma, biotech, or diagnostics
• Demonstrated experience leading data-focused teams in a matrixed, cross-functional organization within a regulated environment
• Proven people management experience, with the ability to build, develop, and retain high-performing teams
• Practical experience with data governance, documentation, and execution standards in regulated settings (e.g. GxP, GDPR, audit readiness)
• Working knowledge of cloud-based data platforms or modern data management environments
• Working knowledge of AI/ML data requirements for model development and validation, with the ability to partner effectively with pathology, computer vision & AI, and data science teams
• Strong execution mindset, with the ability to bring and maintain structure, clarity, and accountability at scale
• Collaborative leadership style, with clear and pragmatic communication across scientific, technical, and operational stakeholders

Desirable

• Experience supporting diagnostic or digital health development, including exposure to regulatory pathways (e.g. FDA, EMA, IVDR)
• Familiarity with large-scale digital pathology datasets (whole slide images, annotations, metadata) and their operational challenges
• Awareness of digital pathology standards and tooling (e.g. DICOM, OME-TIFF, annotation platforms)

Impact

In this role, you will be instrumental in building the operational and data delivery foundation that connects computational pathology research with clinical and diagnostic impact. Your work will ensure that pathology workflows and imaging data are executed, structured, and leveraged to accelerate discovery, improve clinical trial decision-making, and deliver validated diagnostic tools that advance patient care.

What you can expect:

• 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

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.