Principal Machine Learning Scientist - Drug Discovery Analytics

Revolution Medicines is a clinical-stage precision oncology company focused on developing novel targeted therapies to inhibit frontier targets in RAS-addicted cancers. The Principal Machine Learning Scientist will lead advanced machine learning approaches that accelerate small-molecule drug discovery. This role sits at the intersection of data science, chemistry, and biology, transforming complex datasets into predictive models for target discovery and compound design.

Working closely with experimental scientists, develop cutting-edge modeling approaches that integrate chemical, biological, and phenotypic data. Design predictive models, deploy innovative algorithms, and translate insights into actionable decisions. Advance a data-driven discovery strategy to improve the speed and success of medicines for RAS-driven cancers.

Partner with medicinal chemists to guide compound design and optimization. Collaborate with biologists to interpret experimental datasets and generate mechanistic hypotheses. Work with data scientists and ML engineers to deploy models into scalable discovery workflows.

Integrate heterogeneous datasets including chemical structure, screening data, imaging, phenotypic screening, structural biology, and molecular simulation outputs. Provide scientific leadership by defining ML strategies and driving adoption of innovative modeling in multidisciplinary teams. Join outstanding Revolutionaries in a tireless commitment to patients with RAS signaling pathway mutations.