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Process Modeling Engineer

Job in Wickliffe, Lake County, Ohio, 44092, USA
Listing for: Lubrizol Corporation
Full Time position
Listed on 2026-06-03
Job specializations:
  • Engineering
    Process Engineer
Salary/Wage Range or Industry Benchmark: 90000 - 120000 USD Yearly USD 90000.00 120000.00 YEAR
Job Description & How to Apply Below

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

How You’ll Make an Impact

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.

The Process Modeling Engineer plays a critical role in optimizing and transforming manufacturing performance through advanced process modeling, simulation, and data-driven analysis. This role develops and deploys both physics-based and data-based models to support process design, scale-up, troubleshooting, optimization, and long-term strategic planning. The engineer also leads the creation of modeling standards, training programs, and strategic frameworks that elevate modeling capabilities across the organization.

In

this role, you will:
1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
Required Qualifications that Enable Your Success
  • 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,…
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