Industrial Engineering Analytics Engineer (Manufacturing Systems & Modeling)

• Job Title: Industrial Engineering Analytics Engineer (Manufacturing Systems & Modeling)
• Location: Pittsburgh, PA (Onsite)
• Duration: 12+ Months

• Required Skills
• :Greenfield or brownfield project experience (good to have
• )Equipment plannin
• gCapacity plannin
• gLabour plannin
• gCAPEX management (good to have
• )Supplier validatio
• nCapital investments – ROI, IRR, NPV, and cost-benefit analysi
• sDesign and maintain OEE model
• sSupport factory ramp-up, installation, and operational readiness through model validation and performance trackin
• gMaterial plannin
• gPFME
• ALean Manufacturin
• gSix Sigm
• aLayout planning (good to have
• )Simulation tools experience (not mandatory
• )Strong expertise in Exce
• lKnowledge of AI-driven tools (good to have

• )
• J
• D:The Industrial Engineering Analytics Engineer will lead the development and application of advanced analytical models to drive manufacturing efficiency, capacity planning, and co
• stoptimizatio
• n.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 operation
• s.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 environment

s.

• Role Overv
• iew:The Industrial Engineering Analytics Engineer will lead the development and application of advanced analytical models to drive manufacturing efficiency, capacity planning, and cost optimizat
• ion.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 environme

• nts.
• Key Responsibil
• itiesDevelop and own integrated IE models that connect capacity, labor, material flow, PFEP, and cost (COGS) to support factory planning and opera
• tionsBuild and maintain capacity models (target vs. forecast vs. gated capacity), incorporating cycle time, OEE, yield losses, and bottleneck ana
• lysisDevelop labor models to optimize headcount, utilization, and labor cost (LOH) across production sy
• stemsCreate and evaluate business cases for capital investments, including ROI, IRR, NPV, and cost benefit ana
• lysisLead COGS modeling, including labor, overhead, scrap, and process-driven cost compo
• nentsDevelop and track scrap and yield models, quantifying cost impact and identifying improvement opportun
• itiesDesign and maintain OEE models (availability, performance, quality) to drive operational efficiency and continuous improv
• ementPerform buffer and WIP analysis to optimize inline and interline storage, reduce bottlenecks, and stabilize production
• flowDevelop process flow diagrams (PFDs) and value stream maps to represent manufacturing systems and identify inefficie
• nciesIntegrate PFEP (Plan for Every Part) data into models to optimize material flow, storage, and line-side delivery strat
• egiesSupport factory layout, site planning, and material flow decisions through data-driven insights and mod
• elingPerform scenario analysis and sensitivity studies to evaluate production strategies and capacity expansion
• plansUtilize and/or develop factory simulation models (e.g., FlexSim, AnyLogic, Simio) to analyze throughput, bottlenecks, and system perfor
• manceSupport factory ramp-up, installation, and operational readiness through model validation and performance tra
• ckingCollaborate with cross-functional teams (Manufacturing, Operations, Supply Chain, Fin
• ance,Engineering) to align models with real-world constraints and business
• needsTranslate complex analytical outputs into clear, executive-level insights and recommenda
• tionsCollaborate 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-m

• aking
• AI & Data S
• ystemsIntroduce and implement AI-driven tools and platforms to enhance industrial engineering analytics and decision-
• makingDesign and manage scalable data models and data architecture for IE, capacity, labor, PFEP,and cost ana
• lyticsDevelop standardized systems, frameworks, and governance for data modeling, analytics, and rep
• ortingAutomate data collection, validation, and reporting pipelines using AI and advanced analytics
• toolsEnable predictive analytics and intelligent decision-making for capacity, throughput, and cost optimi
• zationEstablish best practices for data quality, model standardization, and system integration across the organi

• zation
• Basic Qualifi
• cationsBachelor’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 a
• nalysisStrong understanding of manufacturing systems, capacity planning, and industrial engineering pri

• nciples
• Preferred Qualif
• icationsExperience building end-to-end IE models integrating capacity, labor, cost, PFEP, and mater
• ial flowProficiency in capacity modeling, OEE analysis, cycle time studies, and line b
• alancingHands-on experience with PFEP, material flow optimization, and warehouse int
• egrationExperience with factory simulation tools (e.g., FlexSim, AnyLogic
• , Simio)Strong experience in business case development (ROI, I
• RR, NPV)Knowledge of COGS modeling, cost structures, and financial impact
• analysisExperience with data analysis tools (Excel advanced modeling, Python, SQL, Power BI/Tableau, or
• similar)Familiarity with AI/ML applications in manufacturing analytics (pr
• eferred)Familiarity with lean manufacturing and continuous improvement metho

dologies

• Key Skills & Co
• mpetenciesStrong analytical and problem-solving skills with a data-driv
• en mindsetAbility to build scalable models and analytics systems that support both tactical and strategic
• decisionsStrong communication skills to translate complex data into actionabl
• e insightsAbility to work across cross-functional teams and influence decis
• ion-makingAttention to detail with a systems-level understanding of manufacturing
• operationsAbility to manage multiple projects and priorities in a fast-paced e

nvironment