Define the vision, product strategy and roadmap for our AI products in drug discovery (structure-based and ligand-based methods), Own the end-to-end product lifecycle from discovery through delivery and iteration, Translate the complex needs of computational scientists, drug discovery teams, and R&D stakeholders into clear product requirements and user-centric features, Collaborate with cross-functional teams of ML engineers, software engineers, data engineers, and domain experts to deliver AI products based on e.g.OpenFold-3 and a chemistry foundation model (e.g.for ADMET), Represent our AI products in conversations with biopharma customers, technical roadmap discussions, and partner collaborations, Work with users of the AI products (e.g., computational chemists, medicinal chemists, structural biologists) in pharma R&D to deeply understand their workflows, pain points, and unmet needs, Champion a user-first culture by continuously advocating for the needs, workflows, and goals of pharma R&D scientists, Stay on top of AI-driven drug discovery trends (e.g., foundation models, multimodal learning, graph-based representations) to inform product strategy, Define success metrics and measure impact through scientific outcomes, user adoption, and model performance benchmarks
