Industrial Analytics Engineer / Lead
Client: Amazon
Location: Pittsburgh, PA – Onsite
Experience: 8+ Years
Job Description
Amazon is seeking an experienced Industrial Analytics Engineer / Lead with strong expertise in industrial engineering analytics, manufacturing modeling, capacity planning, labor and cost modeling, and process optimization.
The ideal candidate will have hands-on experience building end-to-end industrial engineering models covering capacity, labor, cost, throughput, and operational performance. The candidate should also have strong experience working with manufacturing data, MES, simulation tools, SQL, Python, Excel, and BI platforms.
Responsibilities
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Develop capacity models including OEE, cycle time, throughput, utilization, and bottleneck analysis.
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Develop labor and cost models covering COGS, LOH, ROI, NPV, and IRR.
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Perform manufacturing analytics and identify opportunities for process and throughput optimization.
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Build and execute manufacturing simulations using FlexSim, AnyLogic, or Simio.
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Develop end-to-end IE models covering capacity, labor, cost, and operational constraints.
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Perform PFEP and material flow modeling.
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Conduct scenario analysis, sensitivity analysis, forecasting, and what-if analysis.
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Integrate and analyze shop-floor data, MES data, and analytics systems.
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Develop dashboards and analytical solutions using Power BI or Tableau.
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Use advanced Excel, SQL, and Python for data analysis and modeling.
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Develop business cases and financial models supporting operational improvements and investments.
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Collaborate with manufacturing, operations, engineering, finance, and business stakeholders.
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Identify opportunities to leverage AI/ML-based analytics for manufacturing optimization.
Required Skills
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8+ years of experience in Industrial Engineering Analytics / Manufacturing Analytics / Manufacturing Modeling.
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Strong experience with capacity modeling, OEE, cycle time, and bottleneck analysis.
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Strong experience with labor and cost modeling, COGS, LOH, ROI, NPV, and IRR.
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Manufacturing process optimization and throughput analysis.
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Hands-on experience with FlexSim, AnyLogic, or Simio.
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Advanced Excel.
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Strong SQL and Python skills.
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Experience with Power BI and/or Tableau.
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Experience with PFEP and material flow modeling.
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Experience with scenario analysis, sensitivity modeling, and forecasting.
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Experience developing business cases and financial models.
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Hands-on experience integrating shop-floor data, MES, and analytics systems.
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AI/ML analytics experience is a plus.
Candidate Requirements
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Must be available to work onsite in Pittsburgh, PA.
Candidates requiring visa sponsorship will not be considered.
Strong communication, analytical, problem-solving, and stakeholder-management skills required.
Submission Requirements
Please provide:
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Updated Resume
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LinkedIn Profile
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Current Location
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Total Experience
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Relevant Industrial/Manufacturing Analytics Experience
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Simulation Tools Experience
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SQL/Python/Excel Experience
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Power BI/Tableau Experience
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MES/Shop-Floor Data Experience
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PFEP/Material Flow Experience
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Visa/Work Authorization
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Interview Availability
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Earliest Start Date

