POSITION SUMMARY
You will apply modern Data Engineering and MLOps best practices in a highly collaborative environment You will be a core contributor to our Computational Safety Sciences team, helping drive the next generation of data‑ and AI‑enabled drug safety science. You will focus on automating scientific workflows, curating and engineering AI‑ready datasets, and enabling scalable, reusable AI solutions across functions.. You will work closely with Bioinformaticians, Data Scientists, Toxicologists, and Technology partners to turn complex scientific data into robust, production‑grade AI assets.
POSITION RESPONSIBILITIES
Apply Python and/or R programming to support data processing, visualization, and exploratory analyses in support of computational safety science workflows.
Implement and support machine learning and data science workflows by preparing, structuring, and validating data for AI‑enabled toxicology and safety assessment use cases.
Design, curate, and maintain well‑structured datasets and databases for chemical, biological, and toxicology data, ensuring consistency with Pfizer data standards and quality expectations.
Collaborate closely with toxicologists, pathologists, bioinformaticians, and data scientists to integrate multi‑modal datasets (e.g., chemical structures, in vitro and in vivo data, omics).
Contribute to foundational data architecture efforts by helping implement scalable, reusable data pipelines and AI‑ready data assets.
Follow best practices for data integrity, security, and regulatory compliance, while adopting good coding hygiene, version control, testing, and documentation to support reproducibility.
Communicate results and progress through clear documentation, reports, and presentations, and actively participate in team discussions to continuously improve workflows and approaches.
Stay current with emerging data engineering and computational toxicology methods, with a strong interest in learning and applying new tools and best practices.
BASIC QUALIFICATIONS
MS in Biology, Pharmacology, Toxicology, Computer Science, Physics, Statistics, or a related technical discipline OR
BS and 1+ years of experience building AI powered research applications
Technical Skills:
Experience in R and/or Python for data analysis and modeling.
Proficiency in version control (e.g., Git) and adherence to coding best practices, including structured workflows, documentation, and reproducibility standards.
Experience in database creation, management, and analysis particular with toxicology datasets
Understanding of data architecture principles to support AI workflows.
Foundational knowledge in biology and/or chemistry.
Strong communication, collaboration, and problem-solving skills.
PREFERRED QUALIFICATIONS
Experience working with heterogeneous datasets for basic processing, integration, and analysis.
Exposure to front‑end or visualization tools (e.g. Shiny, Streamlit).
Basic understanding of LLM and RAG concepts is a plus.
Foundational software engineering skills, including writing clean code and using version control.
Familiarity with common Python scientific libraries (e.g., NumPy, pandas).
Interest in AI‑assisted coding tools and modern development workflows.
Contributor to team or academic projects.
Experience supporting prototypes or analyses moving toward reusable solutions.
Exposure to workflow tools (e.g., Nextflow).
PHYSICAL/MENTAL REQUIREMENTS
Ability to communicate and to work on teams
NON-STANDARD WORK SCHEDULE, TRAVEL OR ENVIRONMENT REQUIREMENTS
Limited travel requirements for meetings, trainings, and conferences
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 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.
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Salary: $130000-170000
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