Senior Machine Learning Scientist I, Drug Discovery Analytics

Role: Senior Machine Learning Scientist focused on accelerating drug discovery for RAS-addicted cancers through advanced analytics and AI. Responsibilities: develop predictive models for compound activity, selectivity, ADME/Tox, and phenotypic outcomes; analyze heterogeneous chemical, biological, and phenotypic datasets; collaborate with medicinal chemists and biologists for target discovery and lead optimization; integrate models into discovery workflows. Requirements: PhD in computational biology, chemistry, or related field; 6–10 years applying machine learning to scientific data; expertise in Python, ML frameworks (PyTorch, TensorFlow), data visualization; experience with noisy datasets. Preferred: cheminformatics tools, multi-omics analysis, cloud computing, MLOps. HighValue: oncology, RAS pathway, targeted therapies, clinical development, data-driven discovery ecosystem. WorkSetup: not explicitly specified.