Digital Plant Scientist

Eli Lilly and Company • Lebanon, IN

8d • Onsite

About The Position

The Digital Plant Scientist is part of the Lilly Lebanon API Technical Services / Manufacturing Science (TS/MS) team and provides technical leadership and expertise in the development, implementation, and maintenance of digital solutions which includes models, data systems, and process monitoring tools to support continuous manufacturing operations at the LP1 site throughout startup, implementation, and day-to-day operations. In the project delivery and startup phase (expected 2026–2029), the Digital Plant Scientist role will be fluid and dynamic as we support project delivery, build a new organization, develop and implement the necessary systems and business processes required to support GMP operations, and build the site culture. This will require significant collaboration, creativity, and resilience as the site grows to full-scale GMP manufacturing through startup.

Requirements

• 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 Haves

• 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.

Responsibilities

• Develop, implement, and maintain material tracking models using mathematical and first-principles approaches to support batch genealogy and release processes in continuous manufacturing.
• Design and execute digital solutions for process monitoring, data analysis, and control strategy across MES, DeltaV, and batch record analytics platforms.
• Lead integration of batch data products and analytical/parametric data management solutions using appropriate tools (e.g., Python, SIMCA, R) within a cGMP environment.
• 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.
• 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.
• Develop and implement business processes for the use of models and digital solutions in manufacturing, partnering with QA and Operations to ensure compliance.
• Build technical expertise in continuous manufacturing digital systems and demonstrate strong data-driven decision-making and problem-solving capabilities.

Benefits

• company bonus (depending, in part, on company and individual performance)
• company-sponsored 401(k)
• pension
• vacation benefits
• eligibility for medical, dental, vision and prescription drug benefits
• flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts)
• life insurance and death benefits
• certain time off and leave of absence benefits
• well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities)

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree