Senior Scientist Proteomics Discovery

Overview

At Eli Lilly and Company, we unite caring with discovery to make life better for people around the world. Our global healthcare leadership is reflected in our commitment to breakthrough medicines and community support through philanthropy and volunteerism.

Position Summary

The Senior Scientist Proteomics Discovery in the Multiomics Group, within Discovery Technologies, works on cutting edge pharmaceutical experiments. You will collaborate with Molecular Characterization and Discovery Proteomics teams to design studies, execute analyses, and interpret data that supports innovative research programs.

Responsibilities

• Collaborate with diverse discovery technology teams to develop proteomic platforms.
• Design and execute protein profiling studies using platforms like Olink, Somalogic, Milliplex, and Quanterix.
• Develop scalable workflows for multiplex protein profiling of various sample types.
• Operate, maintain, and optimize platform instrumentation to ensure data quality.
• Implement sample preparation protocols and establish QC methods.
• Drive data analysis using statistical methods, platform tools, and machine learning.
• Generate actionable insights and comprehensive technical reporting.
• Maintain lab safety standards, regulatory compliance, and thorough documentation.

Basic Requirements

• Advanced degree in Biochemistry, Proteomics, Immunology, or related field.
• Hands-on experience with Olink or Somalogic platforms and multiple protein analysis platforms.
• Experience in high throughput laboratory workflows and collaborative research.
• Exceptional analytical skills and meticulous attention to experimental detail.

Additional Preferences

• Proficiency in R or Python for large scale omics data analysis.
• Experience with mass spectrometry-based proteomic workflows and immunoassays.
• Knowledge of spatial proteomics methods and machine learning for biomarker development.

Key skills/competency

• Proteomics
• Discovery
• Multiomics
• Biomarker
• High throughput
• Assay development
• Data analysis
• Machine learning
• Molecular biology
• Collaboration