Research Senior Scientist, Cheminformatics AI/ML
Takeda
August 18, 2026
On-site
Boston, MA
$137,000 - $215,270 USD yearly
Clinical Research and Development
Objective / Purpose:
- Skilled cheminformatic scientist to join cheminformatics team to foster a “prediction-first” culture by integrating cheminformatics, computational chemistry, and machine learning to accelerate drug design.
- Collaborate with medicinal chemistry, DMPK, and AI/ML teams; define a roadmap for computational tools that empower medicinal chemists.
Accountabilities:
- Develop and apply agentic AI solutions for drug discovery, including autonomous or human-in-the-loop workflows integrating scientific reasoning, molecular design, data analysis, and computational tools.
- Identify opportunities across the DMTA cycle for predictive acceleration; build models for molecule design/optimization and extract medchem knowledge from chemical/biological datasets.
- Establish and maintain MLOps capabilities: reproducible training/deployment pipelines, lifecycle orchestration, performance monitoring, versioning, scheduled retraining.
- Build and enable search/analytics across ultra-large chemical databases (scalable ingestion, standardization, indexing, similarity/substructure search, distributed computing).
- Implement innovative computational methods for drug discovery (AI-based discovery, generative chemistry, synthesizable chemical space exploration, DEL data analysis, DEL/ML).
- Act as a trusted thought partner to ideate and execute chemistry strategies aligned to therapeutic goals.
Qualifications:
- PhD in Computational Chemistry, Cheminformatics, Computer Science, or related field; 2+ years in pharma/biotech.
- Experience developing agentic AI systems for drug discovery and integrating/orchestrating chemical/biological databases, foundation models, scientific software tools, and multi-step workflows.
- Hands-on MLOps/model lifecycle management (orchestration, CI/CD, registries, monitoring, version control, deployment in cloud or HPC).
- Experience building/searching ultra-large chemical databases; familiarity with cloud storage, vector search, and chemical indexing desired.
- Programming/scripting: Python, R, C/C++; ability to design/automate scalable workflows.
- Strong cheminformatics toolkit expertise (e.g., RDKit); comprehensive DMTA-cycle knowledge; experience leading DMTA acceleration initiatives.
Benefits:
- U.S. base salary range: $137,000.00–$215,270.00 (plus potential incentives and benefits such as medical/dental/vision, 401(k) match, disability, life insurance, tuition reimbursement, volunteer time off, holidays, well-being benefits, sick time, and paid vacation).
Application Instructions:
- Apply via the “Apply” button.
- Skilled cheminformatic scientist to join cheminformatics team to foster a “prediction-first” culture by integrating cheminformatics, computational chemistry, and machine learning to accelerate drug design.
- Collaborate with medicinal chemistry, DMPK, and AI/ML teams; define a roadmap for computational tools that empower medicinal chemists.
Accountabilities:
- Develop and apply agentic AI solutions for drug discovery, including autonomous or human-in-the-loop workflows integrating scientific reasoning, molecular design, data analysis, and computational tools.
- Identify opportunities across the DMTA cycle for predictive acceleration; build models for molecule design/optimization and extract medchem knowledge from chemical/biological datasets.
- Establish and maintain MLOps capabilities: reproducible training/deployment pipelines, lifecycle orchestration, performance monitoring, versioning, scheduled retraining.
- Build and enable search/analytics across ultra-large chemical databases (scalable ingestion, standardization, indexing, similarity/substructure search, distributed computing).
- Implement innovative computational methods for drug discovery (AI-based discovery, generative chemistry, synthesizable chemical space exploration, DEL data analysis, DEL/ML).
- Act as a trusted thought partner to ideate and execute chemistry strategies aligned to therapeutic goals.
Qualifications:
- PhD in Computational Chemistry, Cheminformatics, Computer Science, or related field; 2+ years in pharma/biotech.
- Experience developing agentic AI systems for drug discovery and integrating/orchestrating chemical/biological databases, foundation models, scientific software tools, and multi-step workflows.
- Hands-on MLOps/model lifecycle management (orchestration, CI/CD, registries, monitoring, version control, deployment in cloud or HPC).
- Experience building/searching ultra-large chemical databases; familiarity with cloud storage, vector search, and chemical indexing desired.
- Programming/scripting: Python, R, C/C++; ability to design/automate scalable workflows.
- Strong cheminformatics toolkit expertise (e.g., RDKit); comprehensive DMTA-cycle knowledge; experience leading DMTA acceleration initiatives.
Benefits:
- U.S. base salary range: $137,000.00–$215,270.00 (plus potential incentives and benefits such as medical/dental/vision, 401(k) match, disability, life insurance, tuition reimbursement, volunteer time off, holidays, well-being benefits, sick time, and paid vacation).
Application Instructions:
- Apply via the “Apply” button.