Hybrid Process Optimization Engineer - Data-Driven Efficiency

Placements24; Gqeberha; Hybrid; ZAR 600,000 - 900,000; Full time

Benefits offered by this job

Hybrid work

Health benefits

Leave allowance

Professional development

Job summary

Placements24 is seeking a Process Optimization Engineer to enhance efficiency and productivity in Port Elizabeth. You will analyze chemical processes, identify bottlenecks, and implement data-driven solutions to reduce costs and environmental impact.

Responsibilities include analyzing data, developing optimization strategies, and performing DOE experiments. Collaboration with plant personnel and reporting to management are essential for measurable improvements.

Qualifications

• Bachelor's degree in Chemical Engineering or equivalent.
• Minimum of 5 years in process optimization, troubleshooting, or continuous improvement roles.
• Strong data analysis skills and ability to interpret complex datasets.
• Experience with SPC and Design of Experiments (DOE).
• Understanding of chemical manufacturing principles and equipment.

Responsibilities

• Analyze process data to identify inefficiencies, deviations, and opportunities for optimization.
• Develop and implement strategies for improving process yield, throughput, and energy efficiency.
• Utilize statistical analysis and modeling techniques to predict and control process performance.
• Collaborate with operations teams to implement optimized process parameters and troubleshoot issues.
• Design and execute experiments (DOE) to validate process improvements and new operating conditions.
• Prepare reports and present findings and recommendations to management and cross-functional teams.

Skills

Analytical thinking

Problem-solving

Communication

Education

Bachelor's degree in Chemical Engineering

Tools

Excel

Minitab

Python/R

Process simulation software

Job description

Placements24 is seeking a Process Optimization Engineer to enhance efficiency and productivity in Port Elizabeth. You will analyze chemical processes, identify bottlenecks, and implement data-driven solutions to reduce costs and environmental impact.

Responsibilities include analyzing data, developing optimization strategies, and performing DOE experiments. Collaboration with plant personnel and reporting to management are essential for measurable improvements.