Director, Translational Data Science, Haematology R&D

Job Title: Director, Translational Data Science, Haematology R&D 
Location: Waltham, MA

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 data science group within Hematology Translational Medicine is leading the application of advanced analytics and artificial intelligence to clinical and multi-omics data, aiming to drive data-informed clinical development and discovery in hematology. Our team empowers cross-functional teams by transforming complex datasets into actionable insights across key areas, including T-cell engagers (TCEs), CAR-T cell therapies, small molecules, and ADCs. By doing so, we shape strategies for clinical trial design, patient selection, and the advancement of personalized medicine. 

We seek a highly skilled and visionary Director or Associate Director to manage the hematology data science team, responsible for shaping and executing the AI and data science strategy within our hematology pipeline. The ideal candidate combines technical mastery in machine learning and foundation models with deep experience in the analysis of clinical and molecular data from hematologic malignancy studies. Your expertise will critically inform decisions from early-phase trials to registration studies. 

You will own the integration of novel data modalities across including genomic testing, ctDNA, and MRD, develop and apply state-of-the-art AI and foundation models to large and complex clinical datasets, and serve as an ambassador both inside and outside the organization. 

Accountabilities:

• Manage a team who are developing, applying, and operationalizing statistical and AI-driven models across clinical and real-world datasets in hematologic malignancies.  

• Work cross-functionally to deliver data that impacts decision making across our AstraZeneca Heme portfolio.  

• Devise strategies for integrating and interpreting multimodal datasets to support our goal of making all data computable (clinical, genomic, transcriptomic, proteomic, imaging, and liquid biopsy) to enhance understanding of patient response/resistance and biomarker development in hematology for assets, especially TCE and CAR-T.  

• Oversee and contribute to the application of foundation models (including transformers, LLMs, and multimodal AI) to support biomarker discovery, response prediction, and clinical trial optimization.  

• Foster strong cross-functional partnerships with translational medicine, clinical development, and biostatistics to ensure data-driven approaches inform trial design, patient stratification, and asset development.  

• Continuously innovate analytical workflows for large-scale, high-dimensional clinical and molecular data, ensuring analytical rigor, reproducibility, and interpretability.  

• Mentor and develop a high-performing data science team, cultivating excellence in scientific communication and collaborative problem-solving.  

• Publish research in high-impact journals and represent AstraZeneca at key scientific meetings.

Essential Skills/Experience:

• PhD (or equivalent) in computational biology, bioinformatics, computer science, biostatistics, or closely related field, plus industry experience (Director 6+ years industry experience; Associate Director, 4+ years industry experience). 

• Demonstrable expertise applying machine learning (including deep learning and foundation models) to clinical, genomic, and/or multi-omics datasets, ideally in hematologic malignancies.  

• Proven leadership analyzing and interpreting datasets