Senior Industrial Analytics Engineer
Amazon.com Services LLC•2h ago
United StatesOnsiteFull-timeSenior Level5+ yrs exp
H-1B verified · 2310 LCAs
Top focus
Analytics Engineer
- Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems
- advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion
- human-robot interaction. The Senior Industrial Engineering Analytics Engineer will lead the development and application of advanced analytical models to drive manufacturing efficiency, capacity planning
- cost optimization. This role is responsible for building and managing integrated IE models that connect capacity, labor, material flow, PFEP
- 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
- AI-driven systems to support large-scale manufacturing environments. Key job responsibilities - Develop and own integrated IE models that connect capacity, labor, material flow, PFEP
- 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
- bottleneck analysis - Develop labor models to optimize headcount, utilization
- labor cost (LOH) across production systems - Create and evaluate business cases for capital investments, including ROI, IRR, NPV
- cost-benefit analysis - Lead COGS modeling, including labor, overhead, scrap
- 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
- 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
- line-side delivery strategies - Support factory layout, site planning
- 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
- system performance - Support factory ramp-up, installation
- 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, PFEP
- cost analytics - Develop standardized systems, frameworks
- governance for data modeling, analytics
- reporting - Automate data collection, validation
- reporting pipelines using AI and advanced analytics tools - Enable predictive analytics and intelligent decision-making for capacity, throughput
- cost optimization - Establish best practices for data quality, model standardization
- system integration across the organization
- Bachelor's degree in Engineering (Industrial or Mechanical), Operations Research
- related fields - 7+ years of experience in industrial engineering analytics, manufacturing modeling
- operations analysis - Strong understanding of manufacturing systems, capacity planning
- industrial engineering principles
- Experience building end-to-end IE models integrating capacity, labor, cost, PFEP
- material flow - Proficiency in capacity modeling, OEE analysis, cycle time studies
- line balancing - Hands-on experience with PFEP, material flow optimization
- 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
- financial impact analysis - Experience with data analysis tools (Excel advanced modeling, Python, SQL, Power BI/Tableau
- similar) - Familiarity with AI/ML applications in manufacturing analytics (preferred) - Familiarity with lean manufacturing and continuous improvement methodologies Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability
- other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications
- location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off
- parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, PA, Pittsburgh - 132,100.00 - 178,800.00 USD annually
Required skills
Python