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

AstraZeneca•Boston, MA

1d•Hybrid

About The Position

The Director, Data Science Operations provides 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 complex early-trial, academic collaboration, and exploratory-study data, including omics, imaging, and clinical measurements. Working in a global matrix, the Director mobilizes cross-functional partners to deliver outcomes across Boston and Cambridge in the US, Cambridge in the UK, and Gothenburg in Sweden. The role provides scientific and technical leadership across collaborations, dependencies, governance decisions, and technical workstreams, and focuses on improving how the organisation works through AI-enabled approaches, including agentic AI orchestration. The position sets the operating model and data capabilities, shapes portfolio priorities and delivery plans, and oversees portfolio risks and capacity. It leads and develops a globally distributed interdisciplinary team, builds partnerships across Early CVRM and R&D, advances data management and governance, and defines technology and AI adoption strategy. The role also provides technical direction and may contribute hands-on to data workflows, pipelines, and analyses when that helps accelerate delivery. The position is based in Boston, Massachusetts. AstraZeneca’s described working approach includes face-to-face engagement in its offices three days per week, with flexibility to balance personal and work commitments.

Requirements

PhD in a quantitative or life science discipline, or equivalent experience.
10+ years of experience in scientific data analysis, bioinformatics, or informatics.
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 organization.
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 and 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 operational model and data capabilities for Early CVRM Data Science & AI, translating them into a value-led portfolio of priorities, delivery plans, and measurable scientific outcomes.
Own an integrated view of portfolio delivery, risk, and capacity to inform resource trade-offs and project sequencing.
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; continuously improve productivity and performance across Data Science & AI and matrix teams.
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 the 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 across the portfolio.
Provide senior technical direction and selective expert oversight, and contribute hands-on to data workflows, pipelines, and analyses where doing so accelerates delivery.