Manufacturing Analytics Engineer

We are seeking an experienced Industrial Engineering Analytics Engineer to support manufacturing systems, factory planning, capacity modeling, labor optimization, and data-driven operational improvements. The ideal candidate will have a strong industrial engineering background, hands-on experience building capacity and labor models, expertise in OEE, and proficiency in advanced Excel, Python, SQL, and Power BI/Tableau. Mandatory Skills 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. Hands-on experience building capacity and labor models from scratch. Strong understanding of OEE (Availability, Performance, and Quality). Advanced Excel modeling, Python, SQL, and Power BI/Tableau or similar analytics tools. Strong analytical and numerical skills with the ability to independently generate reports. Excellent communication skills with the ability to present executive-level insights and recommendations. Key Responsibilities Develop integrated industrial engineering models connecting capacity, labor, and manufacturing costs (COGS). Build and maintain capacity models using cycle time, OEE, yield losses, bottleneck analysis, and production forecasts. Develop labor models to optimize headcount, utilization, and labor costs. Evaluate capital investment business cases using ROI, IRR, NPV, and cost-benefit analysis. Lead COGS modeling, including labor, overhead, scrap, and process-related costs. Develop scrap and yield models to identify cost impacts and improvement opportunities. Design and maintain OEE models to improve manufacturing efficiency. Support factory layout, site planning, and material flow decisions through data analytics. Conduct scenario analysis and sensitivity studies for production strategies and capacity expansion. Develop or utilize factory simulation models using FlexSim, AnyLogic, Simio, or similar tools. Support factory ramp-up, installation, and operational readiness through model validation and performance tracking. Collaborate with Manufacturing, Operations, Supply Chain, Finance, and Engineering teams. Translate complex analytical findings into clear business insights and recommendations. Work with MES and Controls teams to integrate shop-floor data with IE models and operational dashboards. AI & Data Systems Implement AI-driven tools and platforms to improve industrial engineering analytics. Design scalable data models and architecture for capacity, labor, and cost analytics. Develop standardized frameworks for data modeling, analytics, and reporting. Automate data collection, validation, and reporting pipelines. Enable predictive analytics for capacity, throughput, and cost optimization. Establish data quality, model standardization, and system integration best practices. Preferred Qualifications Experience developing end-to-end industrial engineering models integrating capacity, labor, cost, PFEP, and material flow. Hands-on experience with PFEP, material flow optimization, and warehouse integration. Experience with factory simulation tools such as FlexSim, AnyLogic, or Simio. Strong business case development experience involving ROI, IRR, and NPV. Knowledge of COGS modeling, cost structures, and financial impact analysis. Proficiency in advanced Excel, Python, SQL, Power BI, or Tableau. Familiarity with AI/ML applications in manufacturing analytics. Knowledge of Lean Manufacturing and continuous improvement methodologies. Ability to build scalable models supporting both tactical and strategic business decisions. Pay: $55.00 - $60.00 per hour Expected hours: 40.0 per week Work Location: In person

View the full posting and apply