Pfizer
Pharmaceutical Sciences
AIEmbeddedSystemsEngineer
“AI Embedded Systems Engineer at Pfizer. Skills: AI Embedded Systems, Data Operations, Software Development, Python. Understand systems and requirements. Develop data products”
What You'll Achieve.
accelerate our organization towards AI-readiness; enable the adoption of AI in Pharmaceutical Sciences; automation; digitization; contextualization of scientific datasets; support downstream AI/ML use cases; accelerate solution delivery
Industry & Context.
solving complex analyses/problems
May require travel to other PharmSci sites (< 10%), Permanent work authorization in the United States, Work on-site an average of 2.5 days per week or more as needed
What They're Looking For.
Must Have
BS in Biology, Chemistry, Physics, Statistics, Computer Sciences or a related technical discipline, 4+ years of experience in a software development role focused on embedded systems and/or data operations, Master’s degree and 2+ years of experience in a software development role focused on embedded systems and/or data operations, Recent PhD graduate in a related technical discipline, Experience with data handling, integration and analysis, experience with SQL, cloud data warehouses, Experience developing data products and data integration solutions in a research or industry environment, Experience solving complex analyses/problems in a timely fashion, C, C#, Java, Go, Python, communication skills—verbal, written, and presentation
Nice to Have
software engineering, package development, cloud architectures, CI/CD, software engineering tooling, scientific Python stack, Github Copilot, AI-enabled coding tools, taking ideas from prototype to production, regulated industry, software validation practices
What You'll Do.
Understand systems and requirements
Develop data products
Develop custom applications
Develop data analysis pipelines
Develop system integration pipelines
Support GMP compliance
Onboard scientists to data applications
Organize workshops/training
Understand data needs
Integration of datasets
Implementation of new methods
Testing of new methods
Validation of new methods
Data analysis techniques
Data visualization techniques
How You'll Work.
Team & Collaboration
Partner with scientists; Work with robotics teams; Partner with other developers
Communication Scope
verbal; written; presentation
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