Machine Learning Scientist II, Drug Discovery Analytics

Revolution Medicines seeks a Machine Learning Scientist II to accelerate oncology drug discovery by developing predictive models and analytical methods. This hands-on role bridges data science, chemistry, and biology to transform complex datasets into actionable insights for target discovery and compound optimization.

Responsibilities

• Develop and implement machine-learning models addressing compound activity, selectivity, and screening outcomes
• Perform exploratory data analysis and quality assessment on heterogeneous datasets
• Prepare and integrate chemical structure, screening, structural biology, and imaging data
• Collaborate with data engineering and medicinal chemists to translate scientific questions into computational analyses
• Document methods, code, and results to support reproducibility and knowledge sharing

Requirements

• Ph.D. in machine learning, computational biology, chemistry, computer science, statistics, or related quantitative field
• Master's degree with relevant industry experience acceptable
• 6-8 years 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 methods
• Experience working with chemical, biological, imaging, and phenotypic datasets