Process Analytics & Monitoring Engineer

Koch Ag & Energy Solutions, LLC; Wichita (KS); On-site; USD 90,000 - 140,000; Full time

Benefits offered by this job

Medical, dental, vision

Retirement plan

Paid time off

Job summary

Koch Ag and Energy Solutions (KAES) seeks a Process and Analytics Engineer to join the Monitoring and Diagnostics Capability at our Wichita, KS campus. The role focuses on applying engineering and data analytics to detect real-time process and equipment deviations and improve asset performance.

Responsibilities include developing monitoring workflows, utilizing PI Asset Framework and PI Vision, and applying advanced analytics, ML, and scripting (Python, R) as needed.

Qualifications

• Process or reliability industry experience with refinery or related equipment.
• Ability to read and interpret process data and detect anomalies.
• Experience with industrial data systems (OSISoft PI/PI AF, data historians).
• Willing to travel up to 10%.

Responsibilities

• Partner with internal customers to understand business problems and apply engineering and analytical solutions.
• Develop and improve anomaly detection monitoring and complex models with SMEs.
• Create monitoring tools using PI Asset Framework and PI Vision.
• Apply analytics methods (HYSYS, pattern recognition, ML) and scripting as needed.
• Train base organization and SMEs on analytical tools (PI AF, Seeq, HYSYS).
• Coordinate with 3rd party contractors on build-out and execution.
• Collaborate with IT to refine analytical and data systems.
• Screen detected anomalies and communicate issues to sites.

Education

Bachelor’s degree in Chemical Engineering

Tools

OSIsoft PI/PI AF

PI Vision

Seeq

HYSYS

Advanced Pattern Recognition

Machine Learning

Python

R

Job description

Koch Ag and Energy Solutions (KAES) seeks a Process and Analytics Engineer to join the Monitoring and Diagnostics Capability at our Wichita, KS campus. The role focuses on applying engineering and data analytics to detect real-time process and equipment deviations and improve asset performance.

Responsibilities include developing monitoring workflows, utilizing PI Asset Framework and PI Vision, and applying advanced analytics, ML, and scripting (Python, R) as needed.