Director, Data Science Operations – Early Cardiovascular, Renal and Metabolism

AstraZeneca•Boston, MA

3d•$181,570 - $272,355•Hybrid

About The Position

The Director, Data Science Operations will provide operational leadership for the operating model, portfolio delivery, and data capabilities of AstraZeneca’s Early Cardiovascular, Renal and Metabolism (CVRM) Data Science & AI organisation. The team connects human data, disease biology, and advanced analytics to inform portfolio decisions from target discovery through clinical development, working with data from early clinical trials, academic collaborations, and exploratory studies, including omics, imaging, and clinical measurements. Working in a global matrix across Boston and Cambridge in the US, Cambridge in the UK, and Gothenburg in Sweden, the Director will mobilize cross-functional partners and provide scientific and technical leadership across collaborations, dependencies, governance decisions, and technical workstreams. A core focus is optimizing how the organisation works through AI-enabled approaches, including the orchestration of agentic AI. The role sets the operational model and data capabilities, shapes a value-led portfolio and delivery plans, and oversees delivery risks, capacity, and resource trade-offs. It leads and develops a globally distributed interdisciplinary team, builds partnerships with project teams and functional leaders, advises senior leadership on portfolio decisions, drives data-management initiatives, and defines technology and AI adoption strategy. The Director may also provide expert oversight and contribute hands-on to workflows, pipelines, and analyses where this accelerates delivery. The position is based in Boston, Massachusetts. The company’s flexible working approach includes face-to-face engagement in the office three days per week.

Requirements

PhD in a quantitative or life science discipline, or equivalent experience.
At least 10 years of experience in scientific data analysis, bioinformatics, or informatics.
At least 5 years of experience leading interdisciplinary scientific, software engineering, and data teams, with demonstrated accountability for outcomes across multiple teams, functions, and geographies in a matrix organisation.
Experience leading the development and operation of data platforms for internal and external user groups.
Track record of coordinating data collection, curation, harmonization, and processing.
Advanced program and project management capabilities, including establishing agile, iterative delivery practices for scientific and technical teams.
Hands-on understanding of multi-omics and clinical data, processing pipelines, metadata, data quality, and cloud data environments.
Demonstrated experience using AI to optimize team workflows and delivery, including orchestration of agentic AI solutions.
Experience developing and applying data governance, data sharing, and access policies for research and patient data.
Demonstrated ability to strategically influence senior cross-functional stakeholders and translate between scientific, clinical, data, and technology teams.
Ability to operate with autonomy and navigate ambiguity.

Responsibilities

Set the Early CVRM Data Science & AI operating model and data capabilities, translating them into a value-led portfolio of priorities, delivery plans, and measurable scientific outcomes.
Own an integrated portfolio view of delivery, risk, and capacity to inform resource trade-offs and sequencing across projects.
Establish cross-functional governance and ways of working that accelerate high-quality delivery, resolve dependencies, and maximize portfolio value across sites and organizational boundaries.
Anticipate and resolve delivery constraints, escalate material trade-offs, and guide timely decisions that protect scientific impact, quality, and speed.
Mentor, inspire, and develop a globally distributed interdisciplinary team of data scientists and informaticians, and provide matrix leadership across partner teams and sites.
Establish and lead a scalable, agile, multi-site operating model with clear decision rights, accountabilities, priorities, and capacity visibility, continually improving productivity and performance.
Champion professional standards and best practices, including code review, reproducible workflows, and documentation.
Build trusted partnerships with project teams and functional leaders across Early CVRM and R&D to align demand with portfolio priorities, focus resources on high-value scientific opportunities, and engage data science where it can have greatest impact.
Provide strategic counsel and evidence-based recommendations to the Executive Director and Early CVRM leadership on portfolio priorities, investment choices, resource trade-offs, and enterprise-level dependencies.
Lead implementation of data-management initiatives, including data storage, metadata, cataloguing, and access, in partnership with central IT, the R&D Data Office, and data owners.
Translate scientific needs into data requirements and working processes for bringing in, documenting, and accessing data from trials, collaborations, and other sources.
Define and own the technology and AI adoption strategy, prioritizing scalable capabilities that increase productivity, accelerate high-quality decisions, and amplify scientific impact.
Provide senior technical direction and selective expert oversight, and contribute hands-on to data workflows, pipelines, and analyses where this accelerates delivery.