Director, Data Science Operations – Early Cardiovascular, Renal and Metabolism
Full Job Posting
Introduction to Role
The Early CVRM (Cardiovascular, Renal and Metabolism) Data Science & AI team connects human data, disease biology and advanced analytics to inform portfolio decisions from target discovery through clinical development. The team works with complex data from early clinical trials, external academic collaborations and exploratory studies, rich in omics, imaging and clinical measurements.
We are hiring a Director, Data Science Operations to provide operational leadership for the operating model, portfolio delivery and data capabilities of the Early CVRM Data Science & AI organisation. Operating in a global matrix, this role will mobilize cross-functional partners to deliver shared outcomes across Boston and Cambridge, US; Cambridge, UK; and Gothenburg, Sweden. The role provides scientific and technical leadership across multiple collaborations, dependencies, governance decisions and technical workstreams. A core focus is to optimize how the organization works through AI-enabled approaches, including the orchestration of agentic AI.
Accountabilities: Program leadership and delivery
Set the operational model and data capabilities for the Early CVRM Data Science & AI, translating it into a value-led portfolio of priorities, delivery plans and measurable scientific outcomes.
Own the integrated portfolio view delivery risk and capacity to shape 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, escalating material trade-offs and guiding timely decisions that protect scientific impact, quality and speed.
Team leadership
Mentor, inspire and develop a globally distributed, interdisciplinary team of data scientists and informaticians, while providing matrix leadership across partner teams and sites to ensure collective accountability for delivery.
Establish and lead a scalable, agile multi-site operating model with clear decision rights, accountabilities, priorities and capacity visibility, continuously improving productivity and performance across Data Science & AI and matrix teams.
Champion professional standards and best practices such as code review, reproducible workflows and documentation.
Stakeholder partnership
Build trusted partnerships with project teams and functional leaders across Early CVRM and R&D to align demand with portfolio priorities, focus resources on the highest-value scientific opportunities and engage data science at the point of 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.
Data operations
Lead the 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.
Technology and AI
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 as well as contribute hands-on to data workflows, pipelines and analyses where it accelerates delivery.
Essential Skills/Experience
- 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 delivered 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 the 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 to translate between scientific, clinical, data and technology teams
- Ability to operate with autonomy and navigate ambiguity
Where can I find out more?
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The annual base pay (or hourly rate of compensation) for this position ranges from $181,570 to $272,355. 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.
Closing Date
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.
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 delivered 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 the 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 to translate between scientific, clinical, data and technology teams
- Ability to operate with autonomy and navigate ambiguity
About AstraZeneca
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