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Senior Capacity Planner

NVIDIA·Израиль·
В офисеПолная занятостьSupply Chain ManagementElectronics Manufacturing

Lead weekly capacity planning and execution for global boards and systems manufacturing. Analyze constraints, align supply plans, guide capital decisions, and present operational risks and mitigation strategies to senior management.

Обязанности

  • Run the weekly capacity planning cycle, including forecast ingestion, supply alignment, contract manufacturer reviews, and planning outputs
  • Consolidate and validate forecasts, NPI consumption, SKU mappings, manufacturer commitments, and yield data
  • Analyze required versus available capacity, identify bottlenecks, and perform scenario analysis
  • Guide capital investment decisions, rationalize forecast changes, and optimize manufacturing volumes
  • Coordinate planning workflows across supply planning, business units, manufacturers, purchasing, engineering, finance, and NPI teams
  • Partner with IT to integrate planning models with enterprise systems, standardized workflows, and data pipelines
  • Present execution plans, operational risks, and mitigation strategies to senior management
  • Align planning frameworks and execution across teams in the United States, Israel, and Asia-Pacific

Требования

  • 5+ years of experience in capacity planning, supply planning, or high-tech manufacturing operations
  • Experience in semiconductor, high-tech electronics, or server infrastructure manufacturing
  • Bachelor’s degree in industrial engineering, operations, manufacturing management, supply chain, or equivalent technical experience
  • Strong proficiency with Excel, Anaplan, and enterprise planning tools
  • Understanding of AI systems, process design, and data-driven operational solutions
  • Ability to manage cross-functional stakeholders and synthesize complex data for executive decisions

Будет плюсом

  • Master’s degree in industrial engineering, supply chain, operations research, or data science
  • Experience with automated data pipelines or machine learning models for supply chain optimization
  • Experience working across global manufacturing sites and willingness to travel when required

Соответствие

Больше возможностей

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