Industrial Engineering Analytics Engineer

Job Title : Industrial Engineering Analytics Engineer Location: Pittsburg, PAJob Type :Fulltime/c2cSalary : $90k- $130kKey ResponsibilitiesDevelop and own integrated IE models that connect capacity, labor, material flow, PEFP, and cost (COGS) to support factory planning and operationsBuild and maintain capacity models (target vs. forecast vs. gated capacity), incorporating cycle time, OEE, yield losses, and bottleneck analysisDevelop labor models to optimize headcount, utilization, and labor cost (LOH) across production systemsCreate and evaluate business cases for capital investments, including ROI, IRR, NPV, and cost benefit analysisLead COGS modeling, including labor, overhead, scrap, and process-driven cost componentsDevelop and track scrap and yield models, quantifying cost impact and identifying improvement opportunitiesDesign and maintain OEE models (availability, performance, quality) to drive operational efficiency and continuous improvementPerform 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 inefficienciesIntegrate PFEP (Plan for Every Part) data into models to optimize material flow, storage, and line-side delivery strategiesSupport factory layout, site planning, and material flow decisions through data-driven insights and modelingPerform 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 performanceSupport factory ramp-up, installation, and operational readiness through model validation and performance trackingCollaborate with cross-functional teams (Manufacturing, Operations, Supply Chain, Finance,Engineering) to align models with real-world constraints and business needsTranslate complex analytical outputs into clear, executive-level insights and recommendationsCollaborate 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-makingAI & Data SystemsIntroduce 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 analyticsDevelop standardized systems, frameworks, and governance for data modeling, analytics, and reportingAutomate data collection, validation, and reporting pipelines using AI and advanced analytics toolsEnable predictive analytics and intelligent decision-making for capacity, throughput, and cost optimizationEstablish best practices for data quality, model standardization, and system integration across the organization