Enter a job title or keyword
Senior Industrial Analytics Engineer
Job Location:
Job Location:
Pittsburgh, PA - USA
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
7 August 2026 (18 hours ago)
Posted:
Application Deadline:
4 November 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Department:
Job Summary
Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazons scale. Were building revolutionary robotic systems that combine cutting-edge AI sophisticated control systems and 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 whats possible in robotic manipulation locomotion and 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 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 industrial engineering fundamentals with advanced analytics simulation business case development and 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 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 PFEP and 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
- Bachelors 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
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or 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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
The Senior 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 industrial engineering fundamentals with advanced analytics simulation business case development and 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 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 PFEP and 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
- Bachelors 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
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or 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 for more information. If the country/region youre applying in isnt 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 and 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 and parental leave. Learn more about our benefits at PA Pittsburgh - 132100.00 - 178800.00 USD annually
Required Experience:
Senior IC
About Company
Free shipping on millions of items. Get the best of Shopping and Entertainment with Prime. Enjoy low prices and great deals on the largest selection of everyday essentials and other products, including fashion, home, beauty, electronics, Alexa Devices, sporting goods, toys, automotive ... View more
