Pfizer
Biotherapeutics
InformaticsandAIengineer,Biotherapeutics
“Informatics and AI engineer, Biotherapeutics at Pfizer. Skills: Data platform, AI architecture, Machine learning, Agentic AI. Develop modern data platform. Support modern data platform”
Industry & Context.
Complex analyses; Complex problems
Permanent work authorization in the United States, Live within commuting distance, Work on-site an average of 2.5 days per week
What They're Looking For.
Must Have
PhD in Biology, Chemistry, Physics, Statistics or related technical discipline, Master’s degree and 2+ years of experience building AI powered research applications, background in data handling, integration and analysis, Thorough understanding of drug discovery and biology, Research experience developing data products and data integration solutions, Experience solving complex analyses/problems, Experience with LLMs, agentic AI, and MCP/RAG systems, Exceptional programming skills in Python, Experience with data governance rules and data validation, full-stack developer with focus on python and SQL, in-depth database expertise, understanding of ETL frameworks and data warehouse technologies, communication skills—verbal, written
Nice to Have
Proficiency in front-end technologies, Proficiency in browser-based visualization techniques, Expertise in software engineering, Expertise in package development, Expertise in cloud architectures, Expertise in CI/CD, Expertise in software engineering tooling, Nextflow pipeline development, knowledge of Linux systems, knowledge of containerization technologies, knowledge of HPC environments, Familiarity with pertinent libraries within Python scientific stack, Hands-on experience handling, processing, integrating, and analyzing large heterogenous data sets data in a drug discovery research environment, Experience with Claude Code or equivalent, Experience with agentic coding paradigms, Demonstrated ability to communicate complex technical work through publications, presentations, or detailed documentation, Experience taking ideas from prototype to production
What You'll Do.
Develop modern data platform
Support modern data platform
Implement modern data platform
Develop data products
Develop machine learning methods
Develop analysis pipelines
Develop data products
Implement new methods
Enhance metadata tagging
Enhance storage strategy
Organize scientific talks
Strengthen external visibility
Strengthen scientific excellence
Engage with scientific community
How You'll Work.
Team & Collaboration
Cross-functional Data Ecosystem Team; Machine learning experts; Digital organization; External companies; Academic institutions
Communication Scope
Verbal communication; Written communication
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