Asks for

The ad says“Experience applying AI methods to medicinal chemistry or cheminformatics challenges, including work with molecular representations, chemical fingerprints, generative models, transformer architectures, pretraining strategies, property prediction, virtual screening, and ADMET modeling.”
The ad says“Experience applying AI methods to medicinal chemistry or cheminformatics challenges, including work with molecular representations, chemical fingerprints, generative models, transformer architectures, pretraining strategies, property prediction, virtual screening, and ADMET modeling.”
The ad says“Experience applying AI methods to medicinal chemistry or cheminformatics challenges, including work with molecular representations, chemical fingerprints, generative models, transformer architectures, pretraining strategies, property prediction, virtual screening, and ADMET modeling.”
The ad says“Experience applying AI methods to medicinal chemistry or cheminformatics challenges, including work with molecular representations, chemical fingerprints, generative models, transformer architectures, pretraining strategies, property prediction, virtual screening, and ADMET modeling.”
The ad says“Strong proficiency in Python, with hands-on experience using cheminformatics libraries and tools such as RDKit, OpenEye, DeepChem, InChI, and SMILES/SMARTS.”
The ad says“Experience applying AI methods to medicinal chemistry or cheminformatics challenges, including work with molecular representations, chemical fingerprints, generative models, transformer architectures, pretraining strategies, property prediction, virtual screening, and ADMET modeling.”
The ad says“Strong proficiency in Python, with hands-on experience using cheminformatics libraries and tools such as RDKit, OpenEye, DeepChem, InChI, and SMILES/SMARTS.”
The ad says“Experience applying AI methods to medicinal chemistry or cheminformatics challenges, including work with molecular representations, chemical fingerprints, generative models, transformer architectures, pretraining strategies, property prediction, virtual screening, and ADMET modeling.”
The ad says“Strong proficiency in Python, with hands-on experience using cheminformatics libraries and tools such as RDKit, OpenEye, DeepChem, InChI, and SMILES/SMARTS.”
The ad says“Experience applying AI methods to medicinal chemistry or cheminformatics challenges, including work with molecular representations, chemical fingerprints, generative models, transformer architectures, pretraining strategies, property prediction, virtual screening, and ADMET modeling.”
The ad says“Experience applying AI methods to medicinal chemistry or cheminformatics challenges, including work with molecular representations, chemical fingerprints, generative models, transformer architectures, pretraining strategies, property prediction, virtual screening, and ADMET modeling.”
The ad says“Strong proficiency in Python, with hands-on experience using cheminformatics libraries and tools such as RDKit, OpenEye, DeepChem, InChI, and SMILES/SMARTS.”
The ad says“Strong proficiency in Python, with hands-on experience using cheminformatics libraries and tools such as RDKit, OpenEye, DeepChem, InChI, and SMILES/SMARTS.”
The ad says“Strong proficiency in Python, with hands-on experience using cheminformatics libraries and tools such as RDKit, OpenEye, DeepChem, InChI, and SMILES/SMARTS.”
The ad says“Experience applying AI methods to medicinal chemistry or cheminformatics challenges, including work with molecular representations, chemical fingerprints, generative models, transformer architectures, pretraining strategies, property prediction, virtual screening, and ADMET modeling.”
The ad says“Experience applying AI methods to medicinal chemistry or cheminformatics challenges, including work with molecular representations, chemical fingerprints, generative models, transformer architectures, pretraining strategies, property prediction, virtual screening, and ADMET modeling.”

ROLE SUMMARY

As a Principal ML/AI 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.

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.

MINIMUM QUALIFICATIONS

PhD in Cheminformatics, Computational Chemistry, Bioinformatics, Data Science, or a closely related field and a minimum of 4 years of relevant drug discovery experience in a pharmaceutical or biotech environment OR
Master’s degree in Cheminformatics, Computational Chemistry, Bioinformatics, Data Science, or a closely related field and a minimum of 9 years of relevant drug discovery experience in a pharmaceutical or biotech environment
Experience applying AI methods to medicinal chemistry or cheminformatics challenges, including work with molecular representations, chemical fingerprints, 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.
Experience communicating effectively and collaborating with diverse teams
Experience delivering results in a fast-paced environment while managing multiple priorities.

Relocation support available

WORK LOCATION ASSIGNMENT: This is a hybrid role requiring you to live within commuting distance and work on-site an average of 2.5 days per week.


The annual base salary for this position ranges from $106,000.00 to $176,600.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 15.0% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life’s moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site – U.S. Benefits | (uscandidates.mypfizerbenefits.com). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States.





Relocation assistance may be available based on business needs and/or eligibility.

Candidates must be authorized to be employed in the U.S. by any employer.

U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future.

Sunshine Act

Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations. These laws and regulations require Pfizer to provide government agencies with information such as a health care provider’s name, address and the type of payments or other value received, generally for public disclosure. Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act. Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government. If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative.

EEO & Employment Eligibility

Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States.

Pfizer endeavors to make www.pfizer.com/careers accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email disabilityrecruitment@pfizer.com. This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned.

To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.


Research and Development
