Director, Computational Engineering and Engineering Sciences

The Director of Computational Engineering & Engineering Sciences owns Wests 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 organizations ability to establish reusable predictive engineering methodologies that improve engineering decision quality across multiple product platforms and engineering organizations.

Enterprise Predictive Engineering

• Own Wests enterprise Predictive Engineering capability
• Serve as Wests 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.

Organizational Leadership

• Develop and grow Wests 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 Wests 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 Wests 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.

• Bachelors degree in Mechanical Engineering Biomedical Engineering Applied Mathematics Physics Computer Science Engineering Science or related discipline required. Masters degree preferred. Ph.D. desirable.

• 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.

• 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