Advisor/Senior Advisor - Process Engineering and Modeling

Eli Lilly And Company; Bengaluru; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Eli Lilly And Company in Bengaluru is seeking an Advisor to lead modeling and data science efforts for small molecule and peptide drug substance development. The role focuses on mechanistic and data-driven modeling to support digestion of complex processes and tech transfer.

You will mentor teams, apply optimization and ML techniques, and collaborate across site functions to drive robust process understanding and scalable solutions in a global pharma environment.

Qualifications

• Ph.D. in Chemical Engineering or closely related discipline.
• 0-5 years of industry experience in modeling, simulation, process engineering, or data science for pharma.
• Substantial computer modeling expertise for process engineering problems.
• Experience with process development, scale-up, and technology transfer.
• Strong mathematical analysis and problem solving for science/engineering systems.
• Proficiency with JMP, MATLAB, ASPEN, Dynochem or gPROMS.
• Experience programming in Python or R.
• Experience with statistical or machine learning tools; ability to implement custom algorithms.
• Strong interpersonal and cross-functional collaboration, and Agile mindset.

Responsibilities

• Lead modeling activities for small molecule and peptide drug substance development.
• Design model-derived solutions for batch and continuous processes and tech transfer.
• Identify process risks and modeling-based recommendations to teams and management.
• Utilize internal/external modeling and experiments to mitigate risks.
• Provide technical oversight for scale-up and transfer to sites and CDMOs.
• Collaborate to identify data-driven decisions informed by data science and analytics.
• Develop tools to mine patterns in data and guide experiments.
• Communicate model assumptions and results to scientists, engineers, and leadership.
• Mentor teams to promote model-informed development and Agile thinking.

Skills

Mathematical modeling

Python

R

MATLAB

JMP

ASPEN

Dynochem

gPROMS

Machine learning

Communication

Agile mindset

Education

Ph.D. in Chemical Engineering

Tools

JMP

MATLAB

ASPEN

Dynochem

gPROMS

Python

R

Job description

Role Summary

The Advisor - Process Engineering and Modeling will provide technical leadership in modeling, simulation, data science, and process engineering to support small molecule and synthetic peptide drug substance development. The role applies deep scientific, engineering, mathematical, and computational expertise to solve problems in chromatography purification, reaction systems, and other unit operations at both small and large scale.

The successful candidate will demonstrate strong technical depth, broad modeling capability, scientific leadership, and a collaborative approach to solving complex process development and manufacturing challenges.

Key Responsibilities

• Lead modeling activities for small molecule and synthetic peptide drug substance development, including mechanistic modeling, data-driven modeling, simulation, and optimization.
• Design and develop model-derived solutions to support clinical and commercial manufacturing processes, including batch and continuous processes, material supply, registration-enabling process understanding, and robust control strategies.
• Identify and communicate process risks, design opportunities, and modeling-based recommendations to project teams and management to enable sound technical and business decisions.
• Use internal and external modeling and experimental resources to mitigate technical risks before they affect project delivery timelines.
• Partner with product teams to provide technical oversight for process scale-up and technology transfer to internal manufacturing sites and external CDMOs.
• Collaborate across PRD to identify decisions that can be informed by data science, statistical modeling, machine learning, and process engineering analysis.
• Select and apply fit-for-purpose data science tools and methodologies to influence development decisions.
• Develop tools and algorithms to mine patterns in existing data and generate recommendations for future experiments, process questions, and modeling strategies.
• Communicate model assumptions, limitations, results, and recommendations clearly to scientific, engineering, manufacturing, and leadership stakeholders.
• Mentor and influence project teams by promoting model-informed development, scientific rigor, and an Agile mindset.

Required Qualifications

• Ph.D. in Chemical Engineering or a closely related discipline.
• 0-5 years of industry experience in modeling, simulation, process engineering, or data science applied to pharmaceutical process development.
• Substantial computer modeling expertise, including application and/or development of modeling tools for process engineering problems.
• Demonstrated experience with process development, scale-up, and technology transfer to internal manufacturing sites or external CDMOs.
• Strong foundation in mathematical analysis, advanced mathematics, and applied problem solving for science- and engineering-based systems.
• Proficiency with mathematical analysis and process modeling programs such as JMP, MATLAB, ASPEN, Dynochem, or gPROMS.
• Experience programming in scripting languages such as R or Python.
• Experience using statistical or machine learning tools, with the ability to implement custom algorithms as needed.
• Strong interpersonal and communication skills, with the ability to collaborate across functions, influence technical decisions, and drive solutions with an Agile mindset.

Preferred Qualifications

• Experience applying optimization, computational fluid dynamics, and computational chemistry tools to solve process engineering problems.
• Experience with chromatography purification experimentation and modelling.
• Experience designing data-rich experiments using automated lab reactors and process analytical technology probes.
• Experience translating kinetic, thermodynamic, and transport data into process understanding, impurity control strategies, and scale-up recommendations.
• Successful interaction with senior engineering and scientific personnel across matrixed project teams.

Additional Information

• Limited international travel, approximately 2-4%, may be required.
• Work-hour flexibility is required to support collaboration across multiple time zones.
• Location: Bengaluru, India.