Industrial Engineering Analytics Engineer (Manufacturing Systems & Modeling)

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 industrialengineering 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 PFEPand 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

• Bachelors 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