Senior ML/AI Cheminformatics Scientist Full-time

Senior Cheminformatics Data Scientist

As a Senior Cheminformatics Data Scientist within the Computational Absorption, Distribution, Metabolism, and Excretion (cADME) group in Pfizer's Pharmacokinetics, Dynamics, and Metabolism (PDM) organization, you will apply data-driven approaches to address critical challenges in small-molecule drug discovery.

In this role, you will develop, deploy, and continuously improve machine learning models for molecular property prediction and leverage Pfizer's proprietary chemical and biological datasets to inform decision-making across hit-to-lead and lead optimization stages. Your work will directly enable more efficient compound prioritization, improved prediction of ADME properties, and accelerated progression of discovery programs.

Success in this position will be defined by the delivery of robust, validated computational models and workflows that generate actionable insights and measurable impact on project outcomes. You will collaborate closely with cross-functional PDM partners and external collaborators to integrate AI-driven approaches into discovery workflows and maximize the value of Pfizer's industry-leading data assets.

Key Responsibilities

• Develop and apply cheminformatics data-mining algorithms for the analysis of molecular modeling, virtual screening, and structure-activity relationship (SAR) analysis. Process and analyze chemical and biological datasets to evaluate properties such as drug-likeness, ADMET properties, dosing, etc.
• Utilize molecular fingerprints, descriptors, and similarity metrics for compound clustering, classification, and regression.
• Assist in development, maintenance, and monitoring of AI/ML models used for property prediction. Optimize data pipelines for processing and storing chemical structures using cheminformatics toolkits (e.g., RDKit, OpenEye)
• Collaborate with cross-functional teams to integrate computational approaches into curation and analysis workflows
• Maintain best practices in data integrity, reproducibility, and documentation of QSAR AI/ML models

Minimum Qualifications

• PhD in a relevant field OR
• Relevant Master's degree with 2+ years of experience in Cheminformatics, Computational Chemistry, Bioinformatics, Data Science, or a related field.
• Proficiency in Python, with experience with cheminformatics libraries and topics (RDKit, OpenEye, DeepChem, InChI, SMILES/SMARTS).
• Experience working in a structured collaborative data and software development environment (git).Experience using SAR model-building software such as SciKit-Learn, Torch, etc.
• Strong understanding of basic statistical concepts and how to evaluate and track model performance.

Preferred Qualifications

• Experience using DAGs to define data pipelines, e.g., Luigi, Airflow, Dagster, Prefect, Kubeflow.)
• Experience working with relational (SQL) and NoSQL databases for chemical data management.
• Experience working with MLOps tools such as MLFlow, Neptune, or SageMaker.

Physical/mental requirements include the ability to perform mathematical calculations and ability to perform complex data analysis.

Non-standard work schedule, travel or environment requirements include some travel required, relocation support available, and this is a hybrid role requiring you to live within commuting distance and work on-site an average of 2.5 days per week.