Industrial Manufacturing Engineer
25 days ago
Pittsburgh
Job Title: Industrial Manufacturing Engineer \n Location: Pittsburgh, PA (Onsite) \n Duration: 6-12 Months \n \n \n Skills \n :Capacity Planning, Industrial Manufacturing, Material Planning, Greenfield or brownfield project experience, Equipment planning, Labour planning, CAPEX management, PFMEA, Lean Manufacturing, Layout planning, Knowledge of AI-driven tool \n \n s \n Required Skill \n\n • s:Greenfield or brownfield project experience (good to hav\n, • e)Equipment planni\n, • ngCapacity planni\n, • ngLabour planni\n, • ngCAPEX management (good to hav\n, • e)Supplier validati\n, • onCapital investments – ROI, IRR, NPV, and cost-benefit analys\n, • isDesign and maintain OEE mode\n, • lsSupport factory ramp-up, installation, and operational readiness through model validation and performance tracki\n, • ngMaterial planni\n, • ngPFM\n, • EALean Manufacturi\n, • ngSix Sig\n, • maLayout planning (good to hav\n, • e)Simulation tools experience (not mandator\n, • y)Strong expertise in Exc\n, • elKnowledge of AI-driven tools (good to hav\n\n \n e) \n Job Descripti \n\n • on:The Industrial Engineering Analytics Engineer will lead the development and application of advanced analytical models to drive manufacturing efficiency, capacity planning, and c\n, • ostoptimizati\n, • on.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 operatio\n, • ns.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 environmen\n\n \n ts. \n Role Overv \n\n • 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\n, • 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\n\n \n nts. \n Key Responsibili \n\n • ties:Develop and own integrated IE models that connect capacity, labor, material flow, PFEP, and cost (COGS) to support factory planning and opera\n, • tionsBuild and maintain capacity models (target vs. forecast vs. gated capacity), incorporating cycle time, OEE, yield losses, and bottleneck ana\n, • lysisDevelop labor models to optimize headcount, utilization, and labor cost (LOH) across production sy\n, • stemsCreate and evaluate business cases for capital investments, including ROI, IRR, NPV, and cost benefit ana\n, • lysisLead COGS modeling, including labor, overhead, scrap, and process-driven cost compo\n, • nentsDevelop and track scrap and yield models, quantifying cost impact and identifying improvement opportun\n, • itiesDesign and maintain OEE models (availability, performance, quality) to drive operational efficiency and continuous improv\n, • ementPerform buffer and WIP analysis to optimize inline and interline storage, reduce bottlenecks, and stabilize production\n, • flowDevelop process flow diagrams (PFDs) and value stream maps to represent manufacturing systems and identify inefficie\n, • nciesIntegrate PFEP (Plan for Every Part) data into models to optimize material flow, storage, and line-side delivery strat\n, • egiesSupport factory layout, site planning, and material flow decisions through data-driven insights and mod\n, • elingPerform scenario analysis and sensitivity studies to evaluate production strategies and capacity expansion\n, • plansUtilize and/or develop factory simulation models (e.g., FlexSim, AnyLogic, Simio) to analyze throughput, bottlenecks, and system perfor\n, • manceSupport factory ramp-up, installation, and operational readiness through model validation and performance tra\n, • ckingCollaborate with cross-functional teams (Manufacturing, Operations, Supply Chain, Fin\n, • ance,Engineering) to align models with real-world constraints and business\n, • needsTranslate complex analytical outputs into clear, executive-level insights and recommenda\n, • 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\n\n \n aking \n AI & Data Sy \n\n • stems:Introduce and implement AI-driven tools and platforms to enhance industrial engineering analytics and decision-\n, • makingDesign and manage scalable data models and data architecture for IE, capacity, labor, PFEP,and cost ana\n, • lyticsDevelop standardized systems, frameworks, and governance for data modeling, analytics, and rep\n, • ortingAutomate data collection, validation, and reporting pipelines using AI and advanced analytics\n, • toolsEnable predictive analytics and intelligent decision-making for capacity, throughput, and cost optimi\n, • zationEstablish best practices for data quality, model standardization, and system integration across the organi\n\n \n zation \n Basic Qualific \n\n • ations: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 a\n, • nalysisStrong understanding of manufacturing systems, capacity planning, and industrial engineering pri\n\n \n nciples \n Preferred Qualifi \n\n • cations:Experience building end-to-end IE models integrating capacity, labor, cost, PFEP, and mater\n, • ial flowProficiency in capacity modeling, OEE analysis, cycle time studies, and line b\n, • alancingHands-on experience with PFEP, material flow optimization, and warehouse int\n, • egrationExperience with factory simulation tools (e.g., FlexSim, AnyLogic\n, • , Simio)Strong experience in business case development (ROI, I\n, • RR, NPV)Knowledge of COGS modeling, cost structures, and financial impact\n, • analysisExperience with data analysis tools (Excel advanced modeling, Python, SQL, Power BI/Tableau, or\n, • similar)Familiarity with AI/ML applications in manufacturing analytics (pr\n, • eferred)Familiarity with lean manufacturing and continuous improvement metho\n\n \n dologies \n Key Skills & Comp \n\n • etencies:Strong analytical and problem-solving skills with a data-drive\n, • n mindsetAbility to build scalable models and analytics systems that support both tactical and strategic\n, • decisionsStrong communication skills to translate complex data into actionable\n, • insightsAbility to work across cross-functional teams and influence decisi\n, • on-makingAttention to detail with a systems-level understanding of manufacturing o\n, • perationsAbility to manage multiple projects and priorities in a fast-paced en\n\n vironment