The Senior Industrial Engineering Analytics Engineer at Amazon will lead the development of advanced analytical models to enhance manufacturing efficiency and cost optimization. This role focuses on integrating various operational factors such as capacity, labor, and material flow to support data-driven decision-making in large-scale manufacturing environments. The ideal candidate will leverage strong industrial engineering fundamentals and advanced analytics to drive improvements in factory operations. This position offers a unique opportunity to work with cutting-edge robotics systems and collaborate with world-class teams.

• Bachelor's degree in Engineering (Industrial or Mechanical), Operations Research, or related fields
• 7+ years of experience in industrial engineering analytics, manufacturing modeling, or operations analysis
• Strong understanding of manufacturing systems, capacity planning, and industrial engineering principles
• 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

• 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 incorporating cycle time, OEE, yield losses, and bottleneck analysis.
• Develop labor models to optimize headcount, utilization, and labor cost 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 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 and value stream maps to represent manufacturing systems and identify inefficiencies.
• Integrate PFEP 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 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 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.

• Employees at Amazon are often offered comprehensive health benefits—including multiple medical plan options (no pre-existing condition exclusions, 100% covered in-network preventive care), dental and vision plans, a 24/7 medical advice line from day one, expert second-opinion services, and broad mental-health support with several free counseling sessions (including pediatric). Financial wellness typically includes a 401(k) with company match (up to 2%), Restricted Stock Units (equity), FSAs, an emergency savings program, product and partner discounts, and even college-savings and home-purchase programs. Overall, the package is designed to support employees and their families’ health, finances, and day-to-day life.