Machine Learning Scientist II

Revolution Medicines seeks a Machine Learning Scientist II to accelerate oncology drug discovery by developing predictive models and analytical methods for biological and chemical datasets. This hands-on role applies machine learning across target discovery, compound optimization, and translational research, collaborating with experimental teams to generate actionable insights.

Responsibilities

• Develop and implement machine learning models addressing drug discovery questions including compound activity, selectivity, and phenotypic outcomes
• Perform exploratory data analysis and quality assessment on chemical, biological, imaging, and phenotypic datasets
• Prepare, integrate, and preprocess heterogeneous datasets from multiple discovery platforms
• Partner with medicinal chemists and biologists to translate scientific questions into computational analyses
• Document methods, code, and results to support reproducibility and knowledge sharing within discovery teams

Requirements

• Ph.D. in machine learning, computational biology, chemistry, computer science, statistics, or related quantitative field; or M.S. with relevant industry experience
• 6-8 years of experience applying machine learning or data science to scientific datasets
• Demonstrated experience developing, validating, and evaluating predictive or classification models
• Proficiency with supervised learning, deep learning, graph-based, and ensemble modeling approaches
• Experience preparing and integrating heterogeneous datasets from chemistry, biology, imaging, and screening sources
• Strong collaborative skills and ability to communicate results to non-computational scientists