AstraZeneca's Hematology R&D is looking to leverage advanced analytics and AI to drive data-informed clinical development and discovery in hematology, aiming to shape strategies for clinical trial design, patient selection, and personalized medicine.
Requirements
- 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 generated from T-cell engagers (TCE), CAR-T therapies, and liquid biopsy (ctDNA/MRD) platforms.
- High proficiency in statistical programming (e.g., R, Python) and experience leveraging high-performance and cloud computing environments.
- Demonstrated experience or strong understanding of GCP-compliant practices for data analysis, including the application of version control, audit trails, and standardized documentation in environments such as Python and R/RStudio.
- Demonstrated success in implementing integrated genomics and imaging datasets to achieve clinical value using AI.
- Experience with Agentic AI and desire to incorporate it into AZ workflows
- Knowledge of current best practices and emerging technologies for MRD and ctDNA analysis.
Responsibilities
- Manage a team who are developing, applying, and operationalizing statistical and AI-driven models across clinical and real-world datasets in hematologic malignancies.
- 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.
Other
- 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).
- Strong understanding of the clinical landscape and biology of hematologic cancers, especially regarding patient stratification, biomarker development, and therapeutic response/resistance mechanisms.
- Exceptional communication skills, with an ability to explain complex analytical findings to scientific, clinical, and business leaders.
- Track record of high-impact publications and/or open-source contributions in computational biology, AI, or oncology.
- Experience directly leading teams, inspiring collaboration, and executing on a vision in a fast-paced environment.
