Senior 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 Senior Machine Learning Scientist will help accelerate drug discovery through advanced analytics and artificial intelligence. This role develops predictive models that transform complex biological and chemical datasets into actionable insights guiding research decisions.

The position works at the interface of data science, chemistry, and biology to support target discovery, compound optimization, and translational research. Key tasks include designing machine learning models to predict compound activity, selectivity, developability, ADME/Tox, target engagement, and phenotypic screening outcomes. Advanced approaches like deep learning, graph neural networks, and ensemble methods will be applied with rigorous validation.

Daily work involves exploratory data analysis on chemical, biological, and phenotypic datasets, integrating heterogeneous data such as chemical structures, high-content imaging, and structural biology outputs. Patterns and relationships will inform scientific hypotheses. Collaboration with medicinal chemists and biologists translates questions into computational strategies for compound design and lead optimization.

Join outstanding Revolutionaries in a tireless commitment to patients with RAS-mutated cancers. Contribute to building a data-driven discovery ecosystem where data, analytics, and experimentation continuously inform and accelerate one another. Partner with data and ML engineers to integrate models into discovery pipelines.