POSITION SUMMARY
In this role, you’ll apply modern data engineering and MLOps best practices within a highly collaborative environment to advance the next generation of data- and AI-enabled ADME (Absorption, Distribution, Metabolism and Excretion) science. Your key responsibilities will include automating scientific workflows, curating and engineering AI-ready datasets, and enabling scalable, reusable AI solutions across various functions.
POSITION RESPONSIBILITIES
Support data processing, visualization, and exploratory analysis for computational workflows using Python.
Enable machine learning and data science workflows by preparing, structuring, and validating data for AI‑enabled ADME use cases.
Design, curate, and maintain well‑structured datasets and databases for chemical, biological, and toxicology data, aligned with Pfizer data standards and quality expectations.
Contribute to data architecture efforts by implementing scalable, reusable data pipelines and AI‑ready data assets.
Apply best practices for data integrity, security, and regulatory compliance, including version control, testing, documentation, and reproducible code.
Communicate progress and results through clear documentation, reports, and presentations, and contribute to team discussions to improve workflows.
Stay current with emerging data engineering and computational tools, and apply new methods and best practices as appropriate.
BASIC QUALIFICATIONS
M.S. in Computer Science, Data Science, Physics, Statistics, or a related technical discipline OR
B.S. with 2+ years experience building AI‑powered research applications.
Strong communication, collaboration, and problem‑solving skills.
Proficiency in Python for data analysis and modeling (e.g., pandas, NumPy, scikit‑learn).
Experience working in a structured, collaborative data/software development environment, including version control (e.g., Git).
Understanding of data architecture principles that support scalable AI/ML workflows.
Experience deploying tools in a cloud environment (AWS, GCP, or Azure).
PREFERRED QUALIFICATIONS
Experience working with heterogeneous datasets for processing, integration, and analysis.
Exposure to low‑code visualization tools (e.g., Dash, Streamlit).
Understanding of large language model (LLM) and retrieval‑augmented generation (RAG) concepts.
Understanding of basic chemistry concepts and chemical structures.
Experience working in cross domain teams (added)
Experience creating, managing, and using databases.
Experience moving prototypes from development to production
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 or more as needed.
Relocation support available
The annual base salary for this position ranges from $82,700.00 to $137,900.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 10.0% of the base salary. 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 [email protected]. 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.
Research and Development
