Industrial Engineering Analytics Engineer

This Industrial Engineering Analytics Engineer role supports factory planning and operations through integrated analytics models that connect capacity, labor, manufacturing efficiency drivers, and cost. The position is based onsite in Pittsburgh, PA with a competitive hourly rate of USD 50 to 55 and requires 7+ years of relevant experience.

Key Responsibilities

• Develop integrated Industrial Engineering (IE) models that connect capacity, labor, material flow, PFEP, and cost (COGS) for factory planning and operational decision-making.
• Create and apply advanced analytical models to improve manufacturing efficiency, support capacity planning, and enable cost optimization.
• Build capacity models covering target versus forecast versus gated capacity, incorporating cycle time, OEE, yield losses, and bottleneck analysis.
• Develop labor models to optimize headcount, utilization, and labor cost (LOH) across production systems.
• Develop and evaluate business cases for capital investments, including ROI, IRR, NPV, and cost benefit analysis.
• Perform COGS modeling that includes labor, overhead, scrap, and process-driven cost components.
• Design OEE models (availability, performance, and quality) to support operational efficiency and continuous improvement.
• Create process flow diagrams (PFDs) and value stream maps to represent manufacturing systems and identify inefficiencies.
• Design scalable data models and data architecture for IE, capacity, labor, PFEP, and cost analytics.

Required Qualifications

• 7+ years of experience in industrial engineering analytics, manufacturing modeling, or operations analysis.
• Industrial engineering background in greenfield.
• Experience using data analysis tools including advanced Excel modeling, Python, SQL, and Power BI or Tableau.

Technical Tools and Simulation Software

• FlexSim
• Anylogic
• Simio
• Excel
• Python
• SQL
• Power BI
• Tableau

Focus Areas

• IE background in greenfield
• Capacity Planning
• Labor planning