Senior Director Cheminformatics & AI

Director / Senior Director – Cheminformatics & Applied AI

Role Overview

We are seeking an experienced Director/Senior Director of Cheminformatics & Applied AI to lead the application of computational chemistry, cheminformatics, machine learning, and AI to small-molecule drug discovery.

This is a senior scientific leadership role with responsibility for advancing computational approaches that improve hit identification, hit-to-lead, lead optimization, and broader discovery decision-making. The ideal candidate combines deep technical expertise with a strong track record of translating emerging technologies into meaningful research outcomes.

Key Responsibilities

• Lead the development and application of cheminformatics, machine learning, and AI methods for drug discovery.
• Develop computational strategies for hit discovery and optimization across screening and virtual screening approaches.
• Apply AI/ML to complex chemical and biological datasets to generate predictive models, actionable insights, and testable hypotheses.
• Evaluate and implement emerging technologies in AI, generative chemistry, molecular modeling, and data science.
• Partner closely with medicinal chemistry, computational chemistry, biology, biophysics, ADME, and data science teams.
• Provide scientific direction across multiple discovery programs and influence research strategy and priorities.
• Build external collaborations with academic groups, biotechnology companies, technology providers, and CROs.
• Mentor and develop computational scientists and contribute to building high-performing, multidisciplinary teams.
• Communicate scientific strategy, results, and recommendations effectively to senior leadership.

Basic Qualifications

• PhD in Cheminformatics, Computational Chemistry, Computer Science, Chemical Engineering, Pharmaceutical Sciences, or a related field with 4 years of relevant industry experience; or MS/BS with 8 years of equivalent experience.
• Demonstrated experience applying computational or AI/ML approaches to drug discovery.
• Strong understanding of small-molecule discovery and medicinal chemistry principles.
• Experience working in multidisciplinary pharmaceutical or biotechnology environments.

Preferred Qualifications

• Proven leadership experience in cheminformatics, computational chemistry, AI/ML, or data science for drug discovery.
• Track record of applying computational technologies to advance discovery programs.
• Expertise in predictive modeling, molecular representations, virtual screening, generative design, chemical space exploration, or related areas.
• Strong programming skills in Python and SQL.
• Experience with tools such as RDKit, OpenEye, PyTorch, scikit-learn, or comparable technologies.
• Familiarity with modern AI-assisted coding and research tools.
• Strong scientific publication, patent, or conference record.
• Excellent communication and cross-functional leadership skills.
• Experience mentoring scientists and leading complex technical initiatives.
• Understanding of the drug discovery process from target assessment through candidate selection.

Ideal Candidate

The ideal candidate is an innovative, collaborative, and data-driven scientific leader who can bridge AI, computational science, and experimental drug discovery and turn advanced technologies into practical solutions that accelerate the development of new medicines.

Reach out to Sam Shinner to apply