Director, Cheminformatics - Modeling & Informatics

Responsibilities

• Set vision and strategy for cheminformatics capabilities and platforms that accelerate scientific learning and decision-making in drug discovery
• Lead a multi-site team of cheminformatics and data science specialists (data engineering, analytics, scientific software development)
• Develop talent, foster diversity of thought, and build an inclusive, high-performing culture
• Engage stakeholders across the drug discovery spectrum (target identification, chemical biology, lead optimization, safety)
• Translate scientific challenges into scalable data architectures, workflows, and algorithmic approaches
• Drive next-generation cheminformatics workflows using modern technologies (ML incl. generative/predictive modeling, knowledge graphs, emerging AI)
• Ensure developed capabilities are deployed and adopted with project teams and modeling partners
• Partner with IT to co-develop robust, sustainable scientific platforms
• Balance investment in new capabilities with effective utilization of existing solutions
• Collaborate with Bioinformatics, Biostatistics, Quantitative Biology, and Modeling leaders to align strategy and priorities
• Work with Modeling, Structure, and Biophysics to identify cheminformatics opportunities
• Maintain visibility across the discovery portfolio to identify emerging needs

Education & Qualifications

• BS/MS/PhD in a relevant STEM field (cheminformatics, bioinformatics, chemistry/biology, statistics, computational chemistry/biology, data science, AI/ML, computer science, math, etc.)
• PhD + 7+ years (or MS + 9+ years, or BS + 13+ years) applying computational/data science to interdisciplinary drug discovery problems
• 2+ years managerial experience in team building, talent development, and inclusive leadership

Required Skills

• Design/implement modern computational workflows (coding best practices, cloud systems, MLOps/DataOps)
• Strong cheminformatics, data analytics, and data engineering knowledge (early drug discovery)
• Predictive modeling and advanced analytics in a collaborative, matrixed environment
• Collaborate across functions and influence strategy across scientific/technical domains
• Engage effectively with IT to co-develop scalable platforms
• Strong communication and stakeholder engagement skills