Senior Principal AI/ML Cheminformatics Scientist Full-time

AI Cheminformatics Scientist

As the world's leading pharmaceutical company, Pfizer is in the unique position of having some of the largest and most complex chemical and biological data sets available anywhere. The computational absorption, distribution, metabolism and excretion (cADME) group at Pfizer is responsible for maximizing the value of ADME, Safety, and Pharmacology data generated to support drug discovery project teams. As an AI Cheminformatics Scientist, you will apply data-driven approaches to drug discovery-focused chemical and biological problems, apply and develop AI/ML models for molecular property prediction, and analyze and optimize hit to lead and lead optimization strategies from our proprietary knowledge base. You will work closely with both the internal product team and external partners to maximize the value of our data.

Role Responsibilities

• Drive scientific and technical advancement in PDM's AI and cheminformatics capabilities by developing and delivering robust, validated workflows and algorithms that directly support drug discovery. Success will be measured by the implementation of effective AI-driven solutions, demonstrated impact on project outcomes, and the publication or presentation of results.
• Design, build, and deploy innovative cheminformatics and AI workflows for small molecule discovery, with clear deliverables including prioritized compound lists, well-defined chemical libraries, and actionable structure-activity relationship analyses.
• Collaborate closely with medicinal chemists, biologists, and data scientists to integrate computational approaches into experimental and analytical workflows. Success in this area will be reflected by joint project milestones achieved, co-authored publications, and the creation of interdisciplinary solutions that accelerate drug discovery.
• Continuously monitor and evaluate emerging advances in AI, cheminformatics, and computational drug discovery, proactively leading the adoption of promising new methodologies. Contributions will include piloting novel techniques, leading internal workshops or training sessions, and helping set strategic directions for technology adoption.
• Collaborate with cross-functional teams—including medicinal chemists, biologists, and data scientists—to integrate computational solutions into drug discovery workflows.
• Develop novel algorithms and analytical strategies tailored to Pfizer's proprietary datasets and key scientific questions, with measurable outcomes such as validated models, software tools, and contributions to scientific literature or patent filings.

Basic Qualifications

• A Ph.D. or Master's degree in Cheminformatics, Computational Chemistry, Bioinformatics, Data Science, or a closely related field is required.
• 8+ years of experience working in drug discovery within the pharmaceutical or biotechnology industry.
• Demonstrated expertise in applying AI methods to medicinal chemistry or cheminformatics challenges, including work with molecular representations, chemical fingerprints, QSAR, generative models, transformer architectures, pretraining strategies, property prediction, virtual screening, and ADMET modeling.
• Strong proficiency in Python, with hands-on experience using cheminformatics libraries and tools such as RDKit, OpenEye, DeepChem, InChI, and SMILES/SMARTS.
• Proven track record of creatively applying computational techniques to address problems relevant to pharmaceutical research and development.
• Ability to communicate effectively, collaborate with diverse teams, and deliver results in a fast-paced environment while managing multiple priorities.
• Experience working within a structured, collaborative data and software development environment, such as using version control systems like Git.

Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact. Additional Information Relocation support available Work Location Assignment: Hybrid