Informatics and AI Engineer, Biotherapeutics

Role Summary

At Pfizer, our purpose is to deliver breakthroughs that change patients' lives. Our cross-functional Data Ecosystem Team is hiring a data and AI engineer to help build and scale an AI-ready data architecture supporting biotherapeutics labs. You will leverage your expertise to design innovative software and agentic AI solutions that help structure and capture Pfizer's proprietary data, and extract valuable insights from both proprietary and external datasets. You will enable the generation of testable hypotheses across the entire drug discovery value chain.

Role Responsibilities

• Develop, support and implement a modern data platform to enable efficient and scalable correlation and analysis of data for biologic drug modalities.
• Develop innovative data products and machine learning methods for biologics data together with machine learning experts within Pfizer.
• Curate and integrate relevant datasets from the public domain.
• Develop analysis pipelines with appropriate use of agentic AI.
• Develop and deploy data products to meet specific needs through data integration.
• Implement, test, and validate new methods for data analysis and visualization techniques.
• Drive collaborations with external companies and academic institutions.
• Enhance Pfizer biologics data capture, metadata tagging, and storage strategy along with Pfizer's Digital organization.
• Onboard Pfizer colleagues to the data platform and organization of workshops, hackathons, trainings and scientific talks.
• Strengthen external visibility and scientific excellence through publishing / presenting work in reputed journals and conference/workshop venues and engaging with the scientific community.

Basic Qualifications

• PhD in Biology, Chemistry, Physics, Statistics or a related technical discipline OR Master's degree and 2+ years of experience building AI powered research applications.
• Strong background in data handling, integration and analysis.
• Thorough understanding of drug discovery and biology with a particular focus on large molecule therapeutics such as peptides and antibodies.
• Research experience developing data products and data integration solutions as well as a sincere desire to innovate at the nexus of data science and agentic AI for life sciences.
• Experience solving complex analyses/problems in a timely fashion.
• Experience with LLMs, agentic AI, and MCP/RAG systems.
• Exceptional programming skills in Python.
• Experience with data governance rules and data validation.
• Strong experience as a full-stack developer with focus on python and SQL, in-depth database expertise and understanding of ETL frameworks and data warehouse technologies.
• Strong communication skills—verbal, written and presentation; demonstrated ability to communicate at the appropriate technical level with scientists having diverse areas of expertise.

Preferred Qualifications

• Proficiency in front-end technologies and browser-based visualization techniques.
• Expertise in software engineering, package development, cloud architectures, CI/CD, and software engineering tooling.
• Nextflow pipeline development.
• Strong knowledge of Linux systems including containerization technologies and HPC environments.
• Familiarity with pertinent libraries within the Python scientific stack.
• Hands-on experience handling, processing, integrating, and analyzing large heterogenous data sets in a drug discovery research environment.
• Experience with Claude Code or equivalent and agentic coding paradigms.
• Demonstrated ability to communicate complex technical work through publications, presentations, or detailed documentation.
• Experience taking ideas from prototype to production.

Physical/Mental Requirements

Ability to perform complex data analysis.

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.