Remote Chemical Process Optimization Specialist

Placements24

Pretoria

Hybrid

ZAR 1,000,000 - 1,600,000

Full time

5 days ago
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Benefits offered by this job

Home office setup stipend
Annual bonus
Stock options
Flexible working hours
Complete remote work

Job summary

Placements24 seeks an experienced Remote Chemical Process Optimization Specialist to join its globally distributed team. You will leverage analytics and simulation tools to enhance efficiency and sustainability of chemical manufacturing processes across multiple sites.

The role requires autonomous work, collaboration with plant engineers, development of MPC systems, and data-driven improvements. A strong background in process simulation, statistics, and AI applied to process engineering is

Qualifications

  • Advanced degree in chemical engineering or related field.
  • 6+ years in chemical process simulation, modeling and optimization.
  • Experience with gPROMS or Aspen Plus and Python or R.
  • Strong background in statistics, ML, and AI for process engineering.
  • Ability to work independently in a remote environment.
  • Excellent written and verbal communication for virtual collaboration.

Responsibilities

  • Analyze large plant operation data to identify optimization opportunities.
  • Develop and implement MPC and advanced process control strategies.
  • Model and test optimization scenarios using process simulation software.
  • Collaborate remotely with site engineers to implement improvements.
  • Prepare detailed reports and presentations for stakeholders.
  • Stay updated on advances in chemical engineering, simulation, and analytics.

Skills

Data analysis
Machine learning
Process optimization
Remote collaboration
Communication

Education

Master's or PhD in Chemical Engineering or related field

Tools

gPROMS
Aspen Plus
Python
R

Job description

About the Role

Our client is seeking an experienced and self-motivated Remote Chemical Process Optimization Specialist to join their globally distributed team. In this role, you will leverage advanced analytics and simulation tools to enhance the efficiency and sustainability of chemical manufacturing processes across various sites. You will work independently, collaborating virtually with plant engineers and operations teams to identify bottlenecks, propose solutions, and implement data-driven improvements. This position is ideal for a highly analytical engineer who excels in a remote work environment and is passionate about driving operational excellence through digital transformation.

Key Responsibilities
  • Analyze large datasets from plant operations to identify areas for process optimization and cost reduction.
  • Develop and implement advanced process control strategies and model predictive control (MPC) systems.
  • Utilize process simulation software to model and test optimization scenarios in a virtual environment.
  • Collaborate virtually with site teams to troubleshoot process issues and implement improvements.
  • Prepare detailed reports and presentations on findings and recommendations for stakeholders.
  • Stay abreast of the latest advancements in chemical engineering , process simulation, and data analytics.
Requirements
  • Master's or Ph.D. in Chemical Engineering or a closely related quantitative field.
  • Minimum of 6 years of experience in chemical process simulation, modeling, and optimization.
  • Demonstrated expertise in process simulation software (e.g., gPROMS, Aspen Plus) and data analysis tools (e.g., Python, R).
  • Strong understanding of statistical analysis, machine learning , and artificial intelligence applications in process engineering.
  • Proven ability to work autonomously and manage projects effectively in a remote setting.
  • Excellent written and verbal communication skills for virtual collaboration.
Benefits
  • Competitive salary commensurate with experience.
  • Home office setup stipend.
  • Flexible working hours and complete remote work flexibility.
  • Annual bonus and stock options.
  • Access to cutting-edge simulation and analytics platforms.
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