Digital Plant Scientist

Eli Lilly Eli Lilly · Pharma · Lebanon, IN

The Digital Plant Scientist will develop, implement, and maintain digital solutions, including models and data systems, to support continuous manufacturing operations in a cGMP environment. This role involves process monitoring, data analysis, integration of batch data, and collaboration with cross-functional teams to build and validate digital tools for a robust control strategy.

What you'd actually do

  1. Develop, implement, and maintain material tracking models using mathematical and first-principles approaches to support batch genealogy and release processes in continuous manufacturing.
  2. Design and execute digital solutions for process monitoring, data analysis, and control strategy across MES, DeltaV, and batch record analytics platforms.
  3. Lead integration of batch data products and analytical/parametric data management solutions using appropriate tools (e.g., Python, SIMCA, R) within a cGMP environment.
  4. Collaborate cross-functionally with process scientists, process Engineering, QA, IT/Automation, operations, and development to identify, build, and validate digital tools that support a robust control strategy.
  5. Own model lifecycle management including documentation, verification protocols, ongoing monitoring plans, and training for model users to ensure models remain in a verified state and data integrity is maintained.

Skills

Required

  • PhD in Chemistry (Organic, Synthetic, Medicinal, or Analytical) or Engineering; OR BS/MS in a related scientific or engineering discipline with at least 3 years of pharmaceutical manufacturing experience.
  • Demonstrated analytical, statistical, and problem-solving skills applicable to manufacturing science.
  • Strong collaborative skills with the ability to work effectively in cross-functional team environments.
  • Demonstrated verbal and written communication skills, including the ability to facilitate technical discussions with senior stakeholders.

Nice to have

  • Experience building and maintaining models (e.g., chemometric, material tracking, or process models) in a cGMP manufacturing environment.
  • Prior experience with continuous manufacturing processes, including process monitoring and control strategy development.
  • Proficiency in data analysis, visualization, and statistical tools (e.g., Python, R, SIMCA, JMP).
  • Familiarity with manufacturing control systems (MES, DeltaV) and batch record/data integration workflows.
  • Experience with troubleshooting, investigation, root cause analysis, and risk assessment in a cGMP environment.
  • Prior work with cross-functional teams spanning Quality, Manufacturing, Engineering, IT/Automation, and Validation.

What the JD emphasized

  • cGMP environment
  • cGMP manufacturing environment
  • continuous manufacturing