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
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
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 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, 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 https://amazon.jobs/en/benefits.
USA, PA, Pittsburgh - 132,100.00 - 178,800.00 USD annually
USA, TX, Austin - 132,100.00 - 178,800.00 USD annually
