Senior Technical Project Manager, Deep Genomics

• 5+ years of experience in Technical Project Management, including leading complex, multi-stakeholder projects from planning through execution
• Proven experience working with ML or Data Science teams; familiarity with the ML lifecycle, including model training, evaluation, and deployment
• Exceptional organizational and communication skills, with experience engaging stakeholders from engineering, research, and leadership
• Experience working in agile, cross-functional teams
• Comfort operating in a fast-paced, research-driven environment where priorities evolve based on new data and discovery
• Strategic thinking and attention to detail; capable of zooming in and out as needed to support tactical execution and high-level planning

Desirable

• As a Senior Technical Project Manager on the Machine Learning Science (ML Science) team, you will lead the execution of complex, cross-functional projects at the intersection of machine learning, genome biology, and drug discovery
• You’ll play a pivotal role in helping our teams build and deploy ML models that enable key scientific breakthroughs in target identification, molecule design, and therapeutic optimization
• You’ll partner closely with a broad range of stakeholders — including ML Scientists, Bioinformaticians, Statistical Geneticists, Experimental Biologists, Product Managers, Engineers, and Leadership — to ensure ML projects are well-scoped, prioritized, and delivered effectively
• These initiatives span internal model development and high-impact external collaborations, including pharmaceutical partnerships, and require tight coordination across both technical and scientific teams
• You will report to the Chief Information Officer, Brendan Frey, and work with teams across Machine Learning, Target Identification, Engineering, Platform Biology, Platform Technology, Platform Chemistry, Legal, Drug Discovery, and Alliances & Partnerships to drive the successful execution of our ML development goals
• Lead the planning, execution, and delivery of machine learning projects across internal R&D and strategic partnerships
• Drive quarterly and yearly project planning with ML Scientists and cross-functional stakeholders; define clear goals, outcomes, timelines, and resource needs
• Establish and maintain robust project management practices tailored to agile, iterative ML workflows
• Track progress across multiple concurrent initiatives; identify risks and proactively remove blockers to keep teams on track
• Facilitate strong collaboration across research, engineering, and external partner teams
• Ensure clear, timely communication of project status, milestones, and risks to internal and external stakeholders
• Manage and facilitate strategic collaborations with external partners, ensuring alignment, execution, and progress on ML and data-driven initiatives