AI Data Engineer-Peptides and Biologics

Role

The Data Ecosystem Team seeks an AI Data Engineer to build and scale a modern, AI-ready data platform supporting biologics labs. You will design and implement data architectures, develop analysis pipelines and data products, and enable integration and analysis of internal and public datasets to support drug discovery for large-molecule therapeutics.

Key Responsibilities

• Develop, support, and implement a modern data platform for scalable correlation and analysis of biologics data.
• Build data products and machine learning methods for biologics in collaboration with ML experts.
• Process, analyze, and integrate internal in vivo pharmacodynamics and toxicology datasets.
• Curate and integrate relevant public-domain datasets and implement data integration solutions.
• Develop analysis pipelines and roll out data products to meet scientific needs.
• Implement, test, and validate methods for data analysis and visualization.
• Drive collaborations with external companies and academic institutions.
• Define biologics data capture, metadata tagging, and storage strategies with Pfizer’s Digital organization.
• Onboard colleagues to the data platform and organize workshops, hackathons, trainings, and scientific talks.
• Contribute to external visibility through publications and presentations; take prototypes to production.

Requirements

• PhD in Biology, Chemistry, Physics, Statistics or related technical discipline OR Master’s degree plus 2+ years of experience building AI-powered research applications.
• Strong background in data handling, integration, and analysis.
• Thorough understanding of drug discovery and biology, especially large molecule therapeutics (peptides, siRNA, antisense, mRNA, antibodies).
• Research experience developing data products and integration solutions for computational life sciences.
• Exceptional programming skills in Python and strong full-stack development experience focused on Python.
• In-depth database expertise with a focus on Postgres and experience with ETL frameworks.
• Strong verbal, written, and presentation communication skills.
• Experience solving complex analyses in a timely manner and taking ideas from prototype to production.

Preferred Qualifications

• Nextflow pipeline development experience.
• Front-end proficiency (TypeScript, ReactJS) and browser-based visualization techniques.
• Experience with PyTorch and Lightning and working knowledge of Python scientific libraries.
• Experience with LLMs and RAG systems.
• Expertise in software engineering best practices: package development, cloud architectures, CI/CD, and tooling.
• Hands-on experience handling large heterogeneous datasets in a drug discovery research environment.
• Experience with Claude Code or equivalent and vibe coding paradigms.
• Strong publication record and demonstrated scientific contributions.

Location & Compensation

• Hybrid role: must live within commuting distance and work on-site an average of ~2.5 days per week.
• Annual base salary range (U.S.): $106,000.00 to $171,500.00.
• Eligible for Pfizer’s Global Performance Plan with a bonus target of 15% of base salary and participation in share-based long-term incentive programs.
• Comprehensive benefits including retirement contributions, paid time off, parental/medical leave, and medical/dental/vision coverage.