Director, Clinical AI Delivery Operations

AstraZeneca; Gaithersburg (MD); On-site; USD 186,000 - 279,000; Full time

Benefits offered by this job

Qualified retirement programs

Paid time off "vacation" and holidays

Health, dental, and vision coverage

Job summary

AstraZeneca is building a world-class AI for Clinical Development capability. The Senior Specialist will define governance, manage multimodal data, and coordinate delivery from research to regulatory-ready outputs.

This role emphasizes compliance, data quality, and cross-functional collaboration across clinical, regulatory, IT, and data teams. Ideal candidates have 5 years handling complex datasets, familiarity with FAIR data, cloud environments, and MLOps.

Qualifications

• 5 years of experience managing complex scientific or clinical datasets, including multimodal data.
• Experience defining or owning data and/or model management processes, standards, or governance frameworks, ideally in a regulated environment.
• Fluency with FAIR data principles and their application in life sciences.
• Working knowledge of cloud-based data environments, modern data platforms, and dataset management workflows.
• Understanding of AI/ML data requirements for model development, validation, and monitoring.

Responsibilities

• Define, implement, and maintain team-wide standards, SOPs, templates, and checklists for data and model intake, curation, dataset release, documentation, and handover.
• Own the team's approach to data and model governance and quality, including dataset versioning, lineage, and traceability.
• Coordinate data access, transfer, and curation with data owners, management, IT, and external collaborators.
• Run and coordinate operational workflows that move clinical AI work from research to validated outputs and handover to partners.
• Ensure compliance with regulatory, quality, and privacy requirements; support audits and inspections.

Skills

Python

Cloud platforms

MLOps

Data governance

Regulatory compliance

Cross-functional collaboration

Documentation

Data management

Education

Bachelor's degree in data science

Master's degree in related field

Tools

JIRA

Confluence

Job description

About AISI

AI Strategy & Innovation (AISI) sits at the centre of AstraZeneca's R&D AI transformation. Our remit is to build, buy and deliver the AI models and agents that change pipeline outcomes, across discovery, translational science, biomarkers and clinical development.

Role Summary

AstraZeneca is building a world-class AI for Clinical Development capability within the Enterprise AI Unit. It will accelerate the design, conduct, and analysis of clinical trials across our enterprise pipeline. We are seeking an AI Senior Specialist, Clinical AI Delivery Operations, to build and run the operational and method delivery foundation that connects clinical AI research with clinical development and patient impact.

You will make sure that multimodal data, models, and AI outputs are fit for purpose for AI development, scientific and clinical decision-making, and regulatory use. You will also make sure that delivery, regulatory, compliance, and quality standards are met from the start of each project.

You will also develop the team-wide operating processes and governance standards that make AI system and output delivery consistent, auditable, and scalable. You will work with AI scientists and engineers, clinical and regulatory domain experts, IT, data partners, and quality partners.

This team is being built from the ground up. The ideal candidate is organized, dependable, data-driven, and detail-oriented. They are motivated by translating advanced and emerging AI research into governed, compliant methods and processes designed for the highly regulated clinical development and operations settings.

Key Responsibilities

Team Processes and Governance Standards

• Define, implement, and maintain team-wide standards, SOPs, templates, and checklists for data and model intake, curation, dataset release, documentation, and handover.
• Own the team's approach to data and model governance and quality. This covers dataset versioning, lineage and traceability, fit-for-purpose criteria, and quality control.
• Serve as the point of contact for governance, compliance, and quality questions. Keep the team aligned with internal policies and external expectations as they evolve.
• Establish metrics for delivery performance, data and model quality, and compliance, and report on them to team leadership.
• Support audit and inspection readiness for the team's data and AI workflows.

Data Access, Transfer, and Curation

• Coordinate with enterprise data owners, clinical data management, IT, and external collaborators to access and transfer multimodal data, models, and associated metadata.
• Ensure datasets and models meet defined formats, metadata standards, and project requirements for each modality.
• Translate scientific and model development requirements into structured dataset preparation tasks.
• Verify the completeness, accuracy, and quality of datasets in line with SOPs.
• Maintain consistency, traceability, and usability of datasets across projects.

Delivery Operations for Clinical AI

• Run and coordinate the operational workflows that take clinical AI work from research to evidence-backed output. This includes data pooling, subsetting and splitting, annotation consolidation, and reproducible data preparation.
• Support handover of validated datasets, models, and outputs to clinical, regulatory, engineering, and IT partners.
• Manage storage and release of results in approved data environments.

Regulatory, Compliance, and Quality

• Ensure datasets and workflows comply with internal policies and governance frameworks. Examples are data privacy, human biological sample governance, and data access approvals (e.g., iDAP).
• Initiate and coordinate approvals with the Data Enablement, Quality, IT, and Compliance teams.
• Build in the data integrity and audit-readiness expected for regulated work.
• Author and maintain documentation such as data collection plans, data and model lineage records, analysis plans, and reports.
• Manage QC checks, deviations, and issue resolution.

Cross-Functional Collaboration

• Work closely with AI scientists, ML engineers, data scientists, program managers, clinical and regulatory business partners, IT and data teams.
• Communicate clearly about data and model readiness, limitations, and uncertainties to support decisions.

Operational Excellence and Continuous Improvement

• Identify and implement improvements to workflows, tooling, and processes so that delivery scales as the team grows.
• Stay informed about emerging data and model management practices, clinical and multimodal data and model standards, and AI governance expectations.

Desired Profile

Education

• Bachelor's or Master's degree in data science, bioinformatics, health or biomedical informatics, or a related field.
• Experience in clinical data management, life sciences, or healthcare is highly desirable.

Experience

• 5 years of experience managing complex scientific or clinical datasets, including multimodal data.
• Experience defining or owning data and/or model management processes, standards, or governance frameworks, ideally in a regulated environment.
• Fluency with FAIR data principles and their application in life sciences.
• Working knowledge of cloud-based data environments, modern data platforms, and dataset management workflows.
• Understanding of AI/ML data requirements for model development, validation, and monitoring.
• Experience with dataset versioning, reproducible data preparation, and quality control.
• Working knowledge of Python or a similar scripting language for data preparation, automation, and QC.
• Familiarity with data governance, compliance processes, and controlled handling of protected data.
• Proven ability to coordinate delivery across multiple stakeholders and workstreams.
• Familiarity with generative AI or agentic systems in clinical or regulatory settings.
• Experience with MLOps, data pipelines, or model lifecycle documentation.

Desirable

• Knowledge of clinical and regulatory data standards (e.g., CDISC SDTM/ADaM, eCTD, DICOM) and of GxP computerized system validation.
• Experience supporting audits or inspections.
• Working knowledge of Atlassian tools (JIRA, Confluence).

Key Competencie

• Excellent interpersonal, verbal, and written communication skills in an international matrix environment.
• Ability to influence without authority and to gain adoption of standards across scientific and engineering teams.
• Strong execution mindset, with ownership and accountability for high-quality delivery.
• Highly structured and detail-oriented, with strong follow-through.
• Pragmatic, fit-for-purpose problem solving, especially when diagnosing data quality or workflow issues.

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.

The annual base pay for this position ranges from $186,014.40 - $279,021.60 USD Annual [80% - 120% ]. Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles. Benefits offered include qualified retirement programs, paid time off (i.e., vacation, holiday, and leaves), as well as health, dental, and vision coverage in accordance with the terms of the applicable plans.

Why AstraZeneca

Here you will fuse cutting-edge science with advanced AI to move a robust pipeline forward across multiple indications, including programs that aim to change the course of cancer. We bring surprising combinations of experts together—biostatisticians with AI engineers, clinicians with product leaders to make faster, smarter decisions that accelerate breakthrough medicines. Backed by significant investment and a culture that values kindness alongside ambition, you will be trusted to lead, challenged to think boldly, and supported to turn ideas into real-world impact for patients.

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.