Industrial Engineering Analytics Engineer (Manufacturing Systems & Modelling)
Location: Pittsburgh, PA
Onsite
- The Industrial Engineering Analytics Engineer will lead the development and application of advanced analytical models to drive manufacturing efficiency, capacity planning, and cost optimization.
- This role is responsible for building and managing integrated IE models that connect capacity, labour, material flow, PFEP, and cost (COGS) to enable data-driven decision making across factory and site operations.
- The ideal candidate will combine strong industrial engineering fundamentals with advanced analytics, simulation, business case development, and AI-driven systems to support large-scale manufacturing environments.
Basic Qualifications
Bachelor’s degree in Industrial Engineering, Mechanical Engineering, Operations Research, or a related field 7+ years of experience in industrial engineering analytics, manufacturing modelling, or operations analysis
Strong understanding of manufacturing systems, capacity planning, and industrial engineering principles
Preferred Qualifications
- Experience building end-to-end IE models integrating capacity, labour, cost, PFEP, and material flow
- Proficiency in capacity modelling, OEE analysis, cycle time studies, and line balancing
- Hands-on experience with PFEP, material flow optimization, and warehouse integration
- Experience with factory simulation tools (e.g., FlexSim, AnyLogic, Simio)
- Strong experience in business case development (ROI, IRR, NPV)
- Knowledge of COGS modelling, cost structures, and financial impact analysis
- Experience with data analysis tools (Excel advanced modelling, Python, SQL, Power BI/Tableau, or similar)
- Familiarity with AI/ML applications in manufacturing analytics (preferred)
- Familiarity with lean manufacturing and continuous improvement methodologies