Process Modeling Engineer

Shape the Future with Us. At Lubrizol, we’re transforming the specialty chemicals market through science, sustainability, and a culture of inclusion. As part of our global team, you’ll be empowered to make a real impact—on your career, your community, and the world around you.

Job Type: Full-time / On-site

Shift +

Hours:

1st Shift

Location: Wickliffe, Ohio or Deer Park, Texas

Travel: 20% or less

As an Process Modeling Engineer you'll be at the forefront of our innovation, driving specialty chemical solutions forward. You'll collaborate with a diverse group of passionate individuals to deliver sustainable solutions to advance mobility, improve wellbeing, and enhance modern life.

• Modeling & Technical Execution
  • Develop, validate, and maintain physics-based process models (e.g., heat/mass transfer, reaction kinetics, fluid dynamics, unit operations).
  • Build and apply data-driven models using statistical, machine learning, or hybrid modeling approaches to identify trends, correlations, and optimization opportunities.
  • Conduct steady‑state and dynamic simulations for process design, capacity analysis, debottlenecking, and energy efficiency assessments.
  • Support troubleshooting and root cause analysis by using modeling to reproduce plant behavior and test hypotheses.
  • Collaborate with R&D, operations, and process engineering to translate lab/pilot data into full‑scale manufacturing models.
• Standards & Best Practices
  • Develop and maintain modeling standards, documentation practices, and validation protocols to ensure consistency, quality, and sustainability of modeling assets.
  • Establish templates, guidelines, and workflows for physics-based and data-driven modeling across the engineering organization.
  • Lead governance activities to ensure models are used responsibly, accurately, and with defined lifecycle management.
• Training & Capability Development
  • Design and deliver training programs, workshops, and hands‑on sessions for engineers, operators, and technical staff on modeling tools, methodologies, and best practices.
  • Mentor engineering teams on model interpretation, limitations, and appropriate use in decision‑making.
  • Help cultivate a culture of data literacy, model-informed design, and digital fluency across the organization.
• Strategy & Technology Leadership
  • Develop and communicate a strategic roadmap for modeling capabilities, including tool selection, digital technologies, and long-term capability growth.
  • Evaluate and integrate emerging modeling technologies—such as AI/ML, advanced simulation platforms, and digital twin solutions.
  • Collaborate with global engineering and operations leaders to align modeling strategy with broader engineering, manufacturing, and corporate objectives.
  • Provide thought leadership in the areas of advanced analytics, digital process design, and predictive manufacturing.
• Cross-Functional Collaboration
  • Work closely with manufacturing, quality, R&D, EHS, and supply chain teams to ensure models support operational excellence, process safety, and product quality.
  • Support capital project teams with modeling contributions for feasibility studies, conceptual design, and detailed engineering.
  • Present model results and recommendations to technical and non‑technical audiences, including senior leadership.

• Master’s or PhD in Chemical Engineering, Process Modeling, Computational Methods, or related fields.
• 3+ years of experience in process engineering, process modeling, or advanced analytics within chemical, materials, or related manufacturing industries.
• Strong experience with process simulation tools (e.g., Aspen Plus, Aspen HYSYS, CHEMCAD, gPROMS).
• Experience developing data-driven models using tools like Python, MATLAB, JMP, or machine learning platforms.
• Strong foundation in transport phenomena, thermodynamics, kinetics, and unit operations.
• Proficiency in data analysis, statistics, and visualization.
• Experience with dynamic modeling, digital twins, or real-time optimization is a plus.
• Ability to integrate lab, pilot, and plant data into robust model frameworks.
• Strong communication skills with ability to explain complex…