Team Leader in Data Science, Disease Area X

What you'll do

• Lead data science strategy and execution for hypothesis-driven drug discovery programs including study design and analysis.
• Perform multi-omics analytics across genomics, proteomics, single-cell, spatial, and imaging data modalities.
• Translate complex scientific questions into computational strategies using statistical, machine learning, and bioinformatics methods.
• Operationalize the use of generative and agentic AI tools while ensuring scientific rigor and data governance.
• Execute hands-on technical work in software development, data engineering, workflow automation, and scalable pipeline creation.
• Manage, coach, and develop a multidisciplinary team of data scientists and computational biologists.
• Communicate scientific findings and recommendations through internal presentations, publications, and external scientific forums.
• Promote FAIR data practices, reproducible research, and high-quality documentation across the organization.

What we're looking for

• Advanced degree (PhD preferred) in Data Science, Computational Biology, Bioinformatics, or a related quantitative/life sciences field.
• 6+ years of experience applying computational biology, bioinformatics, AI/ML, or data science to drug discovery and research.
• Experience leading and managing teams of data scientists or computational biologists in a matrix environment.
• Demonstrated ability to lead complex analyses using multi-omics datasets including genomics, proteomics, and spatial biology.
• Practical experience with Python or R, GitHub, HuggingFace, and workflow orchestration tools.
• Deep experience with cloud-based or enterprise-scale compute platforms and high-performance computing.
• Experience in data engineering, curation, and maintaining governance standards for proprietary and public datasets.
• Proven ability to influence senior stakeholders and translate analytical results into portfolio-relevant decisions.