Industrial Engineering Analytics Engineer (Manufacturing Systems & Modeling)

• Job Title: Industrial Engineering Analytics Engineer (Manufacturing Systems & Modeling)
• Location: Pittsburgh, PA (Onsite)
• NO Positions: #2
• Job Posting Pay Range $50/hr - $60/hr on C2C

Required Skills:

• 1. Greenfield or brownfield project experience (good to have)
• 2. Equipment planning
• 3. Capacity planning
• 4. Labour planning
• 5. CAPEX management (good to have)
• 6. Supplier validation
• 7. Capital investments – ROI, IRR, NPV, and cost-benefit analysis
• 8. Design and maintain OEE models
• 9. Support factory ramp-up, installation, and operational readiness through model validation and performance tracking
• 10. Material planning
• 11. PFMEA
• 12. Lean Manufacturing
• 13. Six Sigma
• 14. Layout planning (good to have)
• 15. Simulation tools experience (not mandatory)
• 16. Strong expertise in Excel
• 17. Knowledge of AI-driven tools (good to have)

JD:

• 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, labor, material flow, PFEP, and cost (COGS) to enable data-driven decisionmaking 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.
• Role Overview:
• · 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, labor, 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.

• Key Responsibilities
• · Develop and own integrated IE models that connect capacity, labor, material flow, PFEP, and cost (COGS) to support factory planning and operations
• · Build and maintain capacity models (target vs. forecast vs. 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
• · Create and evaluate business cases for capital investments, including ROI, IRR, NPV, and cost benefit analysis
• · Lead COGS modeling, including labor, overhead, scrap, and process-driven cost components
• · Develop and track scrap and yield models, quantifying cost impact and identifying improvement opportunities
• · Design and maintain OEE models (availability, performance, quality) to drive operational efficiency and continuous improvement
• · Perform buffer and WIP analysis to optimize inline and interline storage, reduce bottlenecks, and stabilize production flow
• · Develop process flow diagrams (PFDs) and value stream maps to represent manufacturing systems and identify inefficiencies
• · Integrate PFEP (Plan for Every Part) data into models to optimize material flow, storage, and line-side delivery strategies
• · Support factory layout, site planning, and material flow decisions through data-driven insights and modeling
• · Perform scenario analysis and sensitivity studies to evaluate production strategies and capacity expansion plans
• · Utilize and/or develop factory simulation models (e.g., FlexSim, AnyLogic, Simio) to analyze throughput, bottlenecks, and system performance
• · Support factory ramp-up, installation, and operational readiness through model validation and performance tracking
• · Collaborate with cross-functional teams (Manufacturing, Operations, Supply Chain, Finance,
• · Engineering) to align models with real-world constraints and business needs
• · Translate complex analytical outputs into clear, executive-level insights and recommendations
• · Collaborate with MES and Controls teams to integrate shop-floor data with IE models, ensuring accurate OEE measurement and enabling real-time, scalable dashboards for operational visibility and executive decision-making
• AI & Data Systems
• · Introduce and implement AI-driven tools and platforms to enhance industrial engineering analytics and decision-making
• · Design and manage scalable data models and data architecture for IE, capacity, labor, PFEP,and cost analytics
• · Develop standardized systems, frameworks, and governance for data modeling, analytics, and reporting
• · Automate data collection, validation, and reporting pipelines using AI and advanced analytics tools
• · Enable predictive analytics and intelligent decision-making for capacity, throughput, and cost optimization
• · Establish best practices for data quality, model standardization, and system integration across the organization
• 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 modeling, 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, labor, cost, PFEP, and material flow
• · Proficiency in capacity modeling, 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 modeling, cost structures, and financial impact analysis
• · Experience with data analysis tools (Excel advanced modeling, Python, SQL, Power BI/Tableau, or similar)
• · Familiarity with AI/ML applications in manufacturing analytics (preferred)
• · Familiarity with lean manufacturing and continuous improvement methodologies
• Key Skills & Competencies
• · Strong analytical and problem-solving skills with a data-driven mindset
• · Ability to build scalable models and analytics systems that support both tactical and strategic decisions
• · Strong communication skills to translate complex data into actionable insights
• · Ability to work across cross-functional teams and influence decision-making
• · Attention to detail with a systems-level understanding of manufacturing operations
• · Ability to manage multiple projects and priorities in a fast-paced environment