Research Senior Scientist, Cheminformatics AI/ML

Role: Cheminformatic scientist focused on integrating AI and computational chemistry to accelerate drug discovery at Takeda. Responsibilities: develop agentic AI tools for molecule design, optimize predictive models across drug development stages, build MLOps pipelines, and enable large-scale chemical database analytics. Collaborate closely with global teams in medicinal chemistry, DMPK, and AI/ML to define computational strategies that support innovative medicinal chemistry efforts. Requirements: PhD in Computational Chemistry, Cheminformatics, Computer Science, or related field; 2+ years in pharma/biotech; hands-on experience with AI systems, MLOps, chemoinformatics toolkits (e.g., RDKit), and scalable data engineering; proficiency in Python, R, C/C++; knowledge of DMTA cycle and familiarity with cloud/hpc environments. Preferred: experience with generative chemistry, DNA-encoded libraries, high-performance search technologies, and cloud storage solutions. High-Value: focus on drug design acceleration using AI, predictive modeling, and large chemical datasets; role embedded within drug discovery, emphasizing innovation and computational tools to support early and late-stage development. Location: Cambridge, MA.