AI Data Engineer--Computational Toxicology… at Pfizer · United…

Summary: Pfizer is a leading biopharmaceutical company focused on innovative medicines. They are seeking a Senior Associate AI Data Engineer to contribute to the Computational Safety Sciences team, automating scientific workflows and enabling AI solutions for drug safety science. 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 Required 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 - 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) Required Skills: Python, R, Git, Database management, Data architecture, Toxicology datasets, NumPy, pandas Benefits: Participation in Pfizer’s Global Performance Plan with a bonus target of 10.0% of the base salary, 401(k) plan with Pfizer Matching Contributions, Additional Pfizer Retirement Savings Contribution, Paid vacation, Holiday and personal days, Paid caregiver/parental and medical leave, Health benefits to include medical, prescription drug, dental and vision coverage