This role pays less than
94%
of similar roles. Most pay
$187,437–$256,237
— the shaded band above.
At the midpoint, this role pays about
$141k
versus about
$222k
for comparable roles.
Based on 240 similar postings.
Employer
About Pfizer
Pfizer Inc. is one of the world''s largest biopharmaceutical companies, researching, developing, manufacturing, and marketing medicines and vaccines across multiple therapeutic areas including oncology, cardiology, and infectious diseases. Industry: Biopharmaceuticals
Pfizer currently has
27 open roles
on FindRole.
Listed pay typically runs
$106,000–$176,600
across 27 roles with salary data.
As a Principal ML/AI Cheminformatics Scientist within the Computational Absorption, Distribution, Metabolism, and Excretion group, you will develop, deploy, and improve machine learning models for molecular property prediction. You will leverage proprietary chemical and biological datasets to inform decision-making during hit-to-lead and lead optimization stages of small-molecule drug discovery. Your daily work involves building innovative cheminformatics workflows, creating prioritized compound lists, and performing structure-activity relationship analyses to accelerate project outcomes. To succeed, you must utilize Python along with specialized libraries such as RDKit, OpenEye, DeepChem, InChI, and SMILES/SMARTS. You will apply advanced techniques including molecular representations, chemical fingerprints, generative models, transformer architectures, pretraining strategies, virtual screening, and ADMET modeling. This role solves critical challenges in drug discovery by integrating AI-driven approaches into experimental workflows to improve the prediction of essential pharmacokinetic properties.
Develop, deploy, and improve machine learning models for molecular property prediction and ADME properties.
Build and implement cheminformatics workflows to provide prioritized compound lists and structure-activity relationship analyses.
Utilize proprietary chemical and biological datasets to inform decision-making during hit-to-lead and lead optimization stages.
Create novel algorithms and analytical strategies tailored to specific pharmaceutical research questions and data sets.
Monitor emerging advances in AI and cheminformatics to pilot new methodologies and set strategic technology directions.
Integrate computational solutions into experimental and analytical workflows alongside medicinal chemists and biologists.
Produce validated software tools, scientific publications, or patent filings based on internal research findings.
What we're looking for
A PhD in Cheminformatics, Computational Chemistry, Bioinformatics, Data Science, or a related field and at least 4 years of drug discovery experience.
A Master's degree in Cheminformatics, Computational Chemistry, Bioinformatics, Data Science, or a related field and at least 9 years of drug discovery experience.
Experience applying AI methods to medicinal chemistry or cheminformatics challenges including molecular representations, generative models, and property prediction.
Proficiency in Python with hands-on experience using libraries such as RDKit, OpenEye, DeepChem, InChI, and SMILES/SMARTS.
Proven track record of applying computational techniques to pharmaceutical research and development problems.
Ability to communicate effectively and collaborate with diverse cross-functional teams.
Ability to deliver results in a fast-paced environment while managing multiple priorities.
Must have permanent work authorization to be employed in the United States.
Cheminformatics
Data Science
Machine Learning
Artificial Intelligence
Python
SQL
Deep Learning
Generative AI
Linux
High-Performance Computing
Pandas
R
Data Visualization
Active Learning
Drug-Target Interaction Modeling
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