Associate Director, Cheminformatics

Role Summary

Associate Director, Cheminformatics. Lead Takeda’s cheminformatics platform in AI/ML-driven drug discovery, fostering a prediction-first culture and defining a roadmap for computational tools to empower medicinal chemists.

Responsibilities

• Design, automate and deploy cheminformatics workflows and visualization dashboards to support drug discovery projects.
• Identify opportunities throughout the DMTA cycle where predictive tools can drive acceleration. Build predictive models for molecule design and optimization. Extract medchem design knowledge from large-scale chemical and biological datasets.
• Stay updated with emerging trends in computational chemistry and machine learning as applied to drug discovery. Implement and execute innovative computational methodologies and tools such as AI-based drug discovery, generative chemistry, synthesizable chemical space exploration, DNA Encoded Library (DEL) data analysis and DEL/ML application.
• Mentor junior scientists and ML engineers for their career success. Strategize and plan for building an industry-leading cheminformatics group at Takeda.
• Serve as a trusted thought partner, helping to drive ideation and execution of innovative chemistry strategies that meet Takeda’s therapeutic goals.

Qualifications

• PhD in Computational Chemistry, Cheminformatics, Computer Science or related disciplines, with 6+ years of experience in pharmaceutical or biotech setting.
• Strong expertise in cheminformatics toolkits such as RDKit and proficiency in programming languages (Python, R) and dashboard technologies.
• Solid programming and scripting capabilities (e.g., Python, R, C/C++) with a proven ability to design and automate scalable computational workflows.
• Comprehensive knowledge of the DMTA cycle with demonstrated success in deploying predictive tools across the design process.
• Experience with DEL data analysis and Multi-task DL method is a strong plus.
• Experience managing contractors or direct reports. Experience leading strategic initiatives to accelerate DMTA cycle.

Skills

• Cheminformatics toolkits (RDKit) and programming (Python, R) with dashboard technologies
• AI/ML-driven drug discovery, generative chemistry, DEL data analysis
• Mentorship and team-building in scientific/engineering contexts

Education

• PhD in Computational Chemistry, Cheminformatics, Computer Science or related disciplines

Additional Requirements

• Location: Boston, MA
• Full-time, Exempt