We are seeking a Director of Data Science to lead a high-impact team driving data-driven insights and platform development. The Director will oversee two complementary efforts:
A portfolio delivery team focused on applying computational and bioinformatics approaches to internal and external discovery efforts
A platform development team responsible for building scalable infrastructure, computational tools, and ML/AI-driven capabilities to support ongoing and future research
Key Responsibilities:
Strategic Development
Provide strategic direction for data science initiatives, ensuring alignment with company research goals and priorities across all stages of drug discovery, from target ID and validation to translational studies
Work closely with internal and external discovery teams, bioplatforms, and external partners to support research and translational objectives, balance immediate project needs with long-term platform development, and optimize resource allocation and execution
Team & Organizational Management
Directly manage a small team delivering project-driven analyses across multiple therapeutic areas, and a Platforms lead responsible for delivering scalable, reusable computational tools and data infrastructure
Foster a collaborative, high-accountability culture that encourages scientific rigor, innovation, and cross-functional engagement
Drive recruitment, mentorship, and career development within the data science team
Champion best practices in reproducible research, data governance, and AI/ML model deployment
Technical Leadership & Innovation
Stay current on emerging AI/ML approaches, including structural biology (e.g., AlphaFold-style models), multimodal analytics (e.g., integration of omics, imaging, text), and digital pathology image analysis
Ensure that ML/AI innovations are effectively translated into research impact, working closely with experimental biologists and therapeutic area leads
Guide the application of bioinformatics and statistical methods to functional genomic screens (e.g., CRISPR, RNAi, perturbational assays), as well as scalable computational approaches to target and biomarker discovery and validation
The ideal candidate has worked throughout drug discovery, from target identification and validation, to lead discovery and optimization, through to partnering with translational teams on preclinical and biomarker studies. They bring deep expertise in bioinformatic analysis of high-throughput functional genomic screens and proteomics, stay at the forefront of ML/AI innovations in structural biology, multimodal analytics, and/or imaging, and have a proven track record of leading and mentoring teams in biotech or pharmaceutical settings.
Required
Ph.D. (or equivalent experience) in Bioinformatics, Computational Biology, Machine Learning, or a related field
10+ years of experience in computational biology, bioinformatics, or AI/ML with at least 5 years in biotech or pharma industry
Broad technical fluency across omics, imaging, AI/ML, and statistical modeling approaches
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