R&D Data Scientist

Hexcel Corporation • Salt Lake City, UT

7d • Onsite

About The Position

Hexcel is seeking a Research and Development Data Scientist to lead the development and deployment of digital twin technologies that accelerate material, process, and product innovation. This role will focus on building virtual representations of manufacturing processes, materials, and products using advanced analytics, machine learning, physics-based modeling, and AI. The successful candidate will bridge physical experimentation and digital simulation to improve process performance, reduce development cycles, and support next-generation composite material technologies.

Requirements

• Master's degree in data science, Materials Science, Chemical Engineering, Mechanical Engineering, Applied Mathematics, Physics, or a related technical discipline.
• Minimum 2+ years of experience developing predictive models, digital twins, simulation tools, or advanced analytics solutions in an industrial environment.
• Demonstrated experience creating and validating digital twin or virtual process models using machine learning, statistical modeling, physics-based modeling, or hybrid approaches.
• Experience modeling complex physical, chemical, or manufacturing systems.
• Strong analytical and problem-solving skills with the ability to connect physical processes to data-driven modeling techniques.
• Proficiency in Python, R, or similar programming languages and associated machine learning ecosystems.
• Experience with cloud-based data and AI platforms, preferably Microsoft Azure.
• Strong communication skills with the ability to explain complex modeling concepts to multidisciplinary teams.
• Eligible candidates must be a U.S. citizen.

Nice To Haves

• Experience with Digital Twin platforms, Industrial IoT architectures, or digital thread initiatives.
• Experience with Azure Digital Twins, Azure Machine Learning, Azure IoT, Microsoft Fabric, Synapse, or related Microsoft technologies.
• Experience working with manufacturing data, process optimization, materials development, or composite materials.
• Familiarity with ML Ops, model deployment, model governance, and continuous monitoring frameworks.
• Experience utilizing large language models (LLMs), generative AI, or AI agents to support engineering and scientific workflows.
• Experience applying AI and optimization techniques to material formulation or chemical composition development.

Responsibilities

• Lead the design, development, validation, and deployment of digital twins for manufacturing processes, material systems, and product development programs.
• Develop hybrid modeling approaches that combine physics-based models, first-principles engineering, machine learning, and statistical methodologies.
• Integrate sensor, process, quality, and operational data into digital twin frameworks to improve predictive capabilities and decision-making.
• Design and implement advanced AI, machine learning, and analytics solutions that enhance model accuracy, process control, and product performance.
• Collaborate with scientists, engineers, technicians, and manufacturing teams to translate physical system behavior into scalable digital twin architectures.
• Support experimentation strategies, including Design of Experiments (DOE), active learning, and closed-loop optimization to continuously improve digital twin performance.
• Develop simulation environments for evaluating process changes, material innovations, and manufacturing outcomes before physical implementation.
• Establish model governance practices including validation, uncertainty quantification, monitoring, and lifecycle management of digital twin applications.
• Communicate digital twin insights and recommendations to technical and business stakeholders to drive data-driven innovation and operational excellence.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level