Head of Clinical Data Science, Alexion Quantitative Sciences

Job Title: Head of Clinical Data ScienceLocation: Boston

At AstraZeneca, we pride ourselves on crafting a collaborative culture that champions knowledge-sharing, ambitious thinking and innovation – ultimately providing employees with the opportunity to work across teams, functions and even the globe. 

Recognizing the importance of individualized flexibility, our ways of working allow employees to balance personal and work commitments while ensuring we continue to create a strong culture of collaboration and teamwork by engaging face-to-face in our offices 3 days a week. Our head office is purposely designed with collaboration in mind, providing space where teams can come together to strategize, brainstorm and connect on key projects. 

As AstraZeneca continues to put patients at the forefront of our mission, we are excited for our move to Kendall Square/Cambridge in 2026. Find out more information here: Kendall Square Press Release

Introduction to Role:The Sr Director/Head of Clinical Data Science provides strategic and operational leadership for data science, bioinformatics, and AI/ML functions within the Rare Disease Unit. It drives innovation in clinical development by integrating multi-omics, imaging, and digital health data into unified analytical platforms, establishing robust AI and data governance, and aligning data science strategy with organisational R&D priorities. It owns the future direction of mechanism-centered disease modelling and translational AI within Alexion and sets the vision for the application of innovative statistical and bioinformatics methods. 

Accountabilities:

• Providing strategic leadership for clinical data science, bioinformatics, and AI/ML initiatives across the Rare Disease portfolio, ensuring alignment with R&D objectives. 

• Leading the development of Clinical Data Science strategy within Alexion, contributing to the enterprise-wide data science and AI strategy, and contributing to the Alexion Quantitative Sciences strategy. 

• Building and scaling a high-performing cross-functional team spanning AI, bioinformatics, and translational medicine, accelerating study design and data-driven decision-making. 

• Establishing and coordinating AI and data governance frameworks aligned with regulatory standards (FDA, 21 CFR Part 11, CDISC, GxP), reducing compliance risk across clinical programs. 

• Driving the integration of clinical, omics, imaging, and commercial data into unified analytical platforms, enabling sophisticated analytics and knowledge generation. 

• Leading biomarker discovery and validation efforts across multi-omics (transcriptomics, proteomics, genomics) to support patient stratification and therapeutic advancement. 

• Developing and maintaining data infrastructure — data lakes, knowledge graphs, and wearables pipelines — to create sustainable, scalable capabilities for rare disease research. 

• Partnering with translational medicine and clinical teams to design innovative Phase 1/2 proof-of-concept strategies incorporating omics and digital health technologies. 

• Being responsible for the identification and prioritisation of therapeutic targets through AI-enabled clinical and imaging approaches, advancing candidates to IND. 

• Championing the adoption of digital health solutions, including wearables and imaging, as exploratory and registrational endpoints in clinical trials. 

• Integrating multi-omics datasets into pharmacokinetic (PK) models, improving prediction accuracy and strengthening dose-response insights for rare disease programs. 

• Applying AI/ML and omics-driven disease clustering to guide indication prioritisation and drug re purposing opportunities, expanding pipeline value in rare and metabolic diseases. 

• Serving as a senior leader representing Clinical Data Science in internal governance forums and external collaborations, shaping the strategic direction of data-driven rare disease R&D. 

• Planning and managing complex departmental budget, including forecasting for quarterly, annual, and multi-year cycles, and input to the Strategic Planning process. 

• Leading portfolio-level data science capacity management for the R&D unit and contributing to or leading Alexion Quantitative Sciences pivotal initiatives.  

Essential Skills/Experience:

• PhD or master’s degree

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