Senior Industrial Analytics Engineer

Amazon; Austin (TX); On-site; USD 132,000 - 179,000; Full time

Job summary

Amazon seeks a senior Industrial Engineer to design and manage IE models for capacity, PFEP, labor, and cost analytics in Austin, TX. You will drive factory planning, optimize capacity and headcount, and develop robust business cases for investments.

The role demands 7+ years in IE analytics, strong knowledge of manufacturing systems, and experience with data analytics tools and factory simulations to deliver actionable insights for leadership.

Qualifications

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

Responsibilities

• Develop and own integrated IE models to connect capacity, labor, material flow, PFEP and 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 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 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

Skills

Analytical thinking

Problem solving

Cross-functional collaboration

Education

Bachelor's degree in Industrial or Mechanical Engineering

Tools

Excel (Advanced modeling)

Python

SQL

Power BI

Tableau

AnyLogic/FlexSim familiarity

Job description

Job ID: 10491972 | Amazon.com Services LLC

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, 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 what's possible in robotic manipulation, locomotion, and human-robot interaction.

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

Basic Qualifications

• 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

Preferred Qualifications

• 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