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Manager, Data Analytics — AI Infrastructure

NVIDIA Corporation

Israel, RaananaPosted Oct 29, 2026
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Skills named in this posting

  • Python
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.

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Original posting: jobs.nvidia.com

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NVIDIA Corporation in the RISC-V ecosystem

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Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.

  • NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
  • Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
  • Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage

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