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NVIDIA

Manager, Data Analytics — AI Infrastructure

NVIDIA is hiring a Manager, Data Analytics — AI Infrastructure. Level rates it ; you can apply on NVIDIA.

Level's read on this job

  • Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
  • Tools and skills the posting cites include AI agents.
  • Level classifies it as a mid-level role.
  • Level lists 2,700+ other open roles at NVIDIA.
  • The role was posted in the last few days.

AI in this role

ai-agents

NVIDIA is looking for a Data Analytics Manager to join our Software Architecture team. We turn data from AI factories into insights that shape architecture decisions and improve cluster performance, reliability, and efficiency. You will lead our analytics team and own internal initiatives from identifying user needs through delivery and adoption. A central focus will be building and deploying AI agents for analytics—enabling architects and engineers to explore data, investigate sophisticated questions, and act on trusted findings. We seek a leader who combines analytical depth, product judgment, and the ability to turn ideas into capabilities people use. 

What you’ll be doing: 

  • Hire, mentor, and lead an analytics team, setting technical direction, priorities, and standards for analytical quality. 
  • Partner with architects, engineering, and cluster operations to define critical questions and lead analyses that explain system behavior, uncover bottlenecks, and quantify architectural tradeoffs. 
  • Own the roadmap for internal analytics initiatives, translating user needs into requirements, priorities, and measurable outcomes, and driving delivery and adoption. 
  • Lead the development, evaluation, and deployment of AI agents for data exploration, analytical reasoning, and automated investigation, contributing hands-on as needed. 
  • Deliver reusable analytical capabilities, intuitive tools, and dashboards that support engineering and operational decisions. 
  • Partner with data engineering to ensure the data coverage, quality, and context needed for reliable analysis and effective AI agents. 

What we need to see: 

  • BSc./MSc. in a relevant technical field or equivalent experience. 
  • 8+ overall years in data analytics or related technical roles 
  • 4+ years leading and developing a team. 
  • Strong hands-on expertise in SQL, Python, and distributed data platforms. 
  • Experience building AI-powered analytical tools or agents, with methods for validating their accuracy and reliability. 
  • Demonstrable ability in framing ambiguous problems, validating findings, and driving technical initiatives from requirements through delivery and adoption.  
  • Excellent communication and prioritization skills, with the ability to align stakeholders across domains and influence decisions through evidence. 

Ways to stand out from the crowd: 

  • Experience analyzing GPU-cluster telemetry, infrastructure performance, or reliability. 
  • Experience in technical product management or ownership of internal data products. 
  • Familiarity with semantic data models that connect infrastructure entities, telemetry, and operational context. 
  • Experience deploying agents that combine data queries, statistical analysis, and domain knowledge, with demonstrated impact on users’ work. 

We offer competitive compensation and a comprehensive benefits package, with benefits varying by location. You’ll work alongside architects and engineers tackling complex challenges in AI infrastructure, with the opportunity to build a team and shape how we use AI and data to design better systems. We’d love to hear from you! 

NVIDIA is an equal opportunity employer. We welcome applicants from all backgrounds and are committed to providing reasonable accommodations for candidates with disabilities throughout the application and interview process. Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package.

How we rate this

Manager, Data Analytics — AI Infrastructure at NVIDIA rates 71 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agents

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. Describe a typical day in a role like this one: which parts run through AI directly?
  3. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: AI agents. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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