N

NVIDIA

Designs the chips and software that power AI

New Product Enablement Business System Analyst

Full-TimeUpdated on 10/20/2026Deadline 10/23/26
$168k - $258.8k+ Equity
Expert
Bachelor's, MBA
Santa Clara, CA, USA
In Person
Business & StrategyBusiness Analysis
Company Historically Provides H1B Sponsorship

About the job

Requirements
  • A bachelor's degree in Engineering, Supply Chain, Information Systems, or Operations, or equivalent experience.
  • At least 12 years of experience in NPI, manufacturing operations, supply chain systems, or enterprise systems in a complex hardware environment.
  • Experience in the semiconductor, hardware, or high-tech industry and a strong understanding of product lifecycles from NPI through mass production.
  • Strong working knowledge of supply chain functions, including planning, procurement, manufacturing operations, and partner or external manufacturing execution models.
  • Demonstrated ability to lead cross-functional requirements definition and testing or validation across Operations, IT, Data, Planning, Procurement, Industrial Engineering, and Hardware or Product Engineering.
Responsibilities
  • Gather, define, and confirm business, process, and data needs with stakeholders for IT and Operations system setup, including SAP, SPNR, and SERUS, and readiness for new products and site launches such as LPU.
  • Define end-to-end data and system enablement for new products across the product hierarchy (Wafer, Chip, L6, L8, L10, and L11), and partner with data teams to implement it.
  • Translate requirements into delivery-ready artifacts, such as process flows and data mapping, where relevant.
  • Collaborate with Planning and Procurement to design and develop new planning models, such as buy/sell models, with IT; lead alignment on design tradeoffs to simplify solutions, increase flexibility, and improve execution.
  • Analyze and document requirements and impacts for new planning models, such as buy/sell strategy, and coordinate alignment to simplify planning and improve execution.
  • Partner with Industrial Engineering to understand end-to-end product setup and manufacturing workflows.
  • Partner with Product Engineering and Hardware Engineering to get early visibility into new product introductions and NPI/MP schedules for system enablement and data teams.
  • Identify system and data enablement gaps, such as B2B inaccuracies, and partner with data, IT, and relevant teams to resolve them.
  • Drive corrective actions, including process changes, system enhancements, and governance, to simplify system and data enablement setup.
  • Develop a list of activities needed for new product system and data enablement, such as obtaining product P-codes at a new site.
  • Partner with Test Engineering to enable testing parameters, such as test time, in SERUS and IT systems.
Desired Qualifications
  • An MBA is a plus.
  • Be hands-on and technically deep, understand the rationale behind requirements and tradeoffs, and partner cross-functionally to drive clarity and decisions.
  • Be highly organized with strong attention to detail and able to manage multiple workstreams, dependencies, and timelines.
  • Demonstrate the ability to influence and align diverse partners on decisions and execution.
  • Have strong written and verbal communication skills, including executive updates and daily execution.
  • Use a strong problem-solving and process engineering approach with a bias for action and continuous improvement.

About the company

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify Jobs

Simplify's Take

What believers are saying

  • AI demand is still surging: data center sales rose 117% to $89 billion in the quarter ending July 2026.
  • Stock grants are worth more: shares hit a record in October 2026, up 28% for the year.
  • Engineering dominates hiring: 1,722 of NVIDIA's 2,686 job listings in October 2026 were in engineering.

What critics are saying

  • Big buyers are hedging: Meta's February 2026 agreement covers 6 gigawatts of AMD chips.
  • Financing its buyers is getting harder: lenders pushed back on NVIDIA's $500 billion chip-backed loan plan in October 2026.
  • Staff described long hours: Bloomberg's August 2024 interviews reported seven-day weeks, late nights and shouting matches.

What makes NVIDIA unique

  • Rivals must match its software too: over 7.5 million developers use CUDA and other NVIDIA tools to program its chips.
  • The CEO has a broad direct staff: Jensen Huang says over 60 people report to him, without one-on-ones.
  • People rarely leave: NVIDIA's yearly staff turnover is 3.7%, versus a 21.9% average across the tech industry.

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Benefits

  • Company Equity
  • 401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-1%

2 year growth

-2%
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