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Eli Lilly is seeking a Computational Modeling Engineer to join the Digital Manufacturing Engineering (DME) team within the Corporate Engineering Tech Center. This is a global role based in Hyderabad, supporting Lilly's manufacturing and quality science agenda across more than 110 countries.
The role focuses on developing and deploying discrete event simulation and optimization models to drive decisions for designing new and improving existing manufacturing systems across Lilly's global manufacturing network. Key responsibilities include:
• Develop and deploy discrete event simulation and optimization models for parenteral fill/finish, device assembly, packaging, and material handling operations
• Create capacity, throughput, line-balancing, and bottleneck-analysis models to increase manufacturing capacity, resilience, and compliance
• Develop Digital Twin computational models of discrete manufacturing lines and logistics networks to provide online modeling capabilities to manufacturing facilities
• Deliver sound interpretation of modeling results by maintaining deep knowledge of queueing theory, stochastic processes, scheduling theory, and numerical methods
• Validate model-based solutions against site operating data through empirical testing and shop-floor investigation
• Prepare technical reports documenting work and contributing to the body of knowledge; publish and present work externally when appropriate
• Serve as an internal advocate for simulation-based and model-based methods, fostering adoption through instruction, consultation, and collaboration
• Identify and implement modeling advances by staying current with developments in discrete event simulation and optimization
• Partner with data leads to define data requirements supporting discrete manufacturing models and Digital Twin solutions
• Develop external collaborations to manage workload and gain additional expertise
Lilly's Hyderabad hub is a first-of-its-kind technical center leading the manufacturing and quality science agenda for the global supply network. The DME team provides digital engineering platform ownership, OT data integration, engineering data standardization, and digital manufacturing solutions. Digital manufacturing technologies include digital twins, computational modeling, edge/IoT, and analytics solutions.
QUALIFICATIONS:
Basic Requirements:
• PhD with 4–8 years of experience OR MS degree with 8–15 years of experience in Industrial Engineering, Operations Research, Chemical Engineering, Mechanical Engineering, or related field
• Minimum 4 years of related work experience (graduate research included)
• Experience developing models in one or more of: discrete event simulation, nonlinear programming, mixed-integer linear programming, or dynamic simulation of discrete systems
• Demonstrated working knowledge of queueing theory, stochastic processes, and numerical/optimization methods from which discrete event and optimization models are formulated and solved
Preferred Skills:
• Strong technical writing and presentation skills
• Capability to solve complex issues with minimal supervision
• Experience with capacity analysis, line balancing, scheduling, and logistics optimization in manufacturing
• Experience with commercial software tools such as ExtendSim®, Frontline Solver®, aspenONE®, or equivalent discrete event simulation platforms
• Experience with statistical analysis and data/model fitting using JMP® or similar tools
• Experience developing digital twins of discrete manufacturing lines (parenteral fill/finish, device assembly, packaging)
• Experience working with validated systems and in GMP/pharmaceutical industry environments
• Ability to work well across different cultures and global manufacturing sites
