Senior Cheminformatics ML Scientist — Hybrid Role

Pfizer; Groton (CT); Hybrid; USD 94,000 - 156,000; Full time

Benefits offered by this job

401(k) with Pfizer Matching Contrib.

Relocation assistance

Comprehensive health benefits

Job summary

Pfizer in the United States is seeking a Senior Cheminformatics Data Scientist within the cADME group. You will develop and deploy machine learning models for molecular property prediction, leveraging proprietary datasets to inform hit-to-lead and lead optimization decisions.

You will collaborate with cross-functional PDM teams to integrate AI-driven approaches into discovery workflows, ensuring robust, validated models and measurable impact on project outcomes.

Qualifications

• PhD in Cheminformatics, Computational Chemistry, Bioinformatics or related field or a Master's with 2+ years of experience.
• Strong Python expertise with cheminformatics libraries (RDKit, OpenEye, DeepChem).
• Experience in collaborative data/software environments (git).
• Experience with SAR model-building using SciKit-Learn, Torch, etc.
• Solid understanding of statistics and model evaluation.

Responsibilities

• Develop cheminformatics data-mining for molecular modeling, SAR analysis.
• Process chemical/biological data to evaluate drug-likeness and ADMET.
• Use fingerprints, descriptors, similarity metrics for clustering/classification/regression.
• Assist in development and monitoring of AI/ML models for property prediction.
• Optimize data pipelines for chemical structures using cheminformatics toolkits.
• Collaborate with cross-functional teams to integrate computational workflows.
• Maintain data integrity, reproducibility, and documentation of QSAR/ML models.

Skills

Python

Cheminformatics libraries

RDKit

OpenEye

SciKit-Learn

Torch

Git

Education

PhD in Cheminformatics/Related field

Master's + 2+ years experience

Tools

RDKit

OpenEye

DeepChem

InChI/SMILES

Job description

Pfizer in the United States is seeking a Senior Cheminformatics Data Scientist within the cADME group. You will develop and deploy machine learning models for molecular property prediction, leveraging proprietary datasets to inform hit-to-lead and lead optimization decisions.

You will collaborate with cross-functional PDM teams to integrate AI-driven approaches into discovery workflows, ensuring robust, validated models and measurable impact on project outcomes.