Radnor Director, Computational Engineering and Engineering Sciences PA 19087

Job Summary

The Director of Computational Engineering & Engineering Sciences owns West's enterprise capability for predictive engineering. This role develops and applies engineering sciences, computational methods, simulation, and validated digital engineering methodologies that establish technical confidence, improve engineering decision quality, and reduce dependence on physical iteration throughout early technology evaluation, product engineering, manufacturing development, and customer technical collaboration.

The capability partners closely with Enterprise AI Strategy & Solutions, applying enterprise AI capabilities within engineering to strengthen predictive engineering, engineering methodologies, and engineering decision quality.

This role integrates structural analysis, fluid dynamics, Moldflow, metrology, computational modeling, analytical engineering, and predictive engineering into a unified enterprise capability supporting Central R&D, Operating Units, customers, and external technology partners.

Working across pre-development, Product Engineering, Manufacturing Development, Digital Platforms, and Operating Units, this role partners with engineering organizations to establish predictive engineering methodologies that improve technical confidence and engineering decision quality across the enterprise.

Success is measured by the organization's ability to establish reusable predictive engineering methodologies that improve engineering decision quality across multiple product platforms and engineering organizations.

Essential Duties and Responsibilities

Enterprise Predictive Engineering

• Own West's enterprise Predictive Engineering capability
• Serve as West's enterprise authority for predictive engineering, establishing methodologies, standards, and model validation practices that improve technical confidence and engineering decision quality across multiple engineering Organizations.
• Establish engineering methodologies that improve technical confidence through predictive analysis prior to physical iteration.
• Develop reusable predictive engineering methodologies supporting pre-development, product engineering, manufacturing development, and customer technical collaboration.
• Establish enterprise standards governing computational engineering methods, simulation quality, and engineering model validation.

Predictive Engineering Applications

• Develop enterprise predictive engineering methodologies supporting concept evaluation, technical risk reduction, and early product realization.
• Lead application of structural mechanics, fluid dynamics, Moldflow, multiphysics simulation, optimization, and systems modeling throughout product development.
• Expand predictive engineering practices supporting concept evaluation, feasibility, and product development through simulation, engineering sciences, and validated computational methods.
• Improve engineering decision quality through predictive analysis and engineering trade studies.
• Support architecture evaluation, engineering optimization, and technical risk reduction using computational methods.
• Develop computational methodologies supporting customer collaboration on predictive evaluation of drug-device, drug-container, and material interaction.

Engineering Integration of Enterprise AI

• Define engineering use cases and integrate enterprise AI capabilities into predictive engineering methodologies where they improve technical confidence, engineering productivity, and engineering decision quality.
• Develop engineering methodologies that combine simulation, computational methods, and predictive engineering practices to accelerate technical learning and reduce engineering uncertainty.

Engineering Capability Development

• Integrate Structural Engineering, Fluid Engineering, Moldflow, Metrology, Computational Modeling, and Analytical Engineering into a unified enterprise capability.
• Develop engineering methodologies that reduce dependence on physical prototypes through validated predictive models.
• Establish reusable predictive engineering methodologies, validated engineering models, and computational standards supporting multiple engineering organizations and product platforms.
• Promote collaboration across pre-development, Product Engineering, Manufacturing Development, and Operating Units.

Additional Responsibilities

Organizational Leadership

• Develop and grow West's Predictive Engineering capability through direct technical leadership, strategic partnerships, and selective capability expansion aligned with business demand.
• Develop capability roadmaps, staffing recommendations, and investment strategies aligned with enterprise priorities and demonstrated business demand.
• Promote continuous improvement in engineering methodologies supporting West's strategic growth platforms.
• Ensure compliance with West quality systems and applicable regulatory requirements.
• Build strategic relationships with pharmaceutical customers, software providers, universities, research organizations, and external technology partners to advance West’s enterprise predictive engineering capability.
• Develop the long-term capability strategy for Predictive Engineering, including organization, technology, partnerships, and engineering methodology roadmaps.
• Perform other duties as assigned.

Education

• Bachelor's degree in Mechanical Engineering, Biomedical Engineering, Applied Mathematics, Physics, Computer Science, Engineering Science, or related discipline required. Master's degree preferred. Ph.D. desirable.

Work Experience

• Minimum ten (10) years of engineering experience with significant emphasis on computational engineering, simulation, or predictive engineering.
• Minimum seven (7) years of engineering leadership experience.
• Demonstrated experience applying structural analysis, fluid dynamics, Moldflow, computational modeling, and engineering simulation to complex product development programs.
• Experience establishing enterprise engineering methodologies or technical standards preferred.
• Experience supporting regulated product development strongly preferred.
• Experience collaborating with external customers or partners on predictive modeling, simulation, material interaction, or drug-container / drug-device technical evaluations preferred.
• Demonstrated experience leading multidisciplinary analytical engineering organizations.
• Experience applying enterprise AI capabilities within engineering simulation, optimization, or predictive engineering environments preferred.

Preferred Knowledge, Skills and Abilities

• Expert knowledge of finite element analysis (FEA), computational fluid dynamics (CFD), Moldflow, optimization methods, and systems modeling.
• Strong understanding of engineering sciences supporting regulated product development.
• Experience developing predictive engineering methodologies that improve engineering decision quality.
• Experience integrating enterprise AI capabilities into engineering methodologies supporting simulation, optimization, and engineering decision quality.
• Knowledge of digital engineering, model-based engineering, digital twins, and advanced computational methods.
• Strong understanding of model validation, verification, uncertainty quantification, and engineering best practices.
• Demonstrated ability to translate computational analysis into practical engineering decisions.
• Experience building reusable enterprise engineering capabilities rather than project-specific analytical support.
• Strong executive communication skills with the ability to explain complex technical concepts to engineering, commercial, and executive leadership.
• Demonstrated ability to influence engineering strategy across multiple organizations without direct reporting authority. #LI-NJ1

Travel Requirements

Physical Requirements

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