Senior Data Scientist – Eda Datacenter Observability And Reliability

Invidia

Us, CA, United States
Base: 184,000 usd - 287,500 usd for level 4, 224,0...
Hybrid
Python and sql proficiency
Large-scale observability data analysis
Statistical and machine learning modeling
You will work closely with hardware, software, and infrastructure engineering teams to analyze large-scale observability and telemetry data generated by EDA workloads running across global CPU and GPU compute clusters

Job Summary

  • You will work closely with hardware, software, and infrastructure engineering teams to analyze large-scale observability and telemetry data generated by EDA workloads running across global CPU and GPU compute clusters.
  • Our work will directly inform operational decisions and long-term planning for NVIDIA’s rapidly growing EDA environment.
  • You will build statistical and machine learning models for anomaly detection, failure pattern analysis, and reliability improvement to enhance datacenter scaling and performance.

Matching Summary

You will work closely with hardware, software, and infrastructure engineering teams to analyze large-scale observability and telemetry data generated by EDA workloads running across global CPU and GPU compute clusters.

Salary

Base: 184,000 USD - 287,500 USD for Level 4, 224,000 USD - 356,500 USD for Level 5; Bonus/Equity: Eligible for equity; Benefits: Eligible for benefits

Skills & Requirements

Must-have

  • Python and SQL proficiency
  • Large-scale observability data analysis
  • Statistical and machine learning modeling
  • EDA datacenter monitoring
  • Hardware reliability analysis
  • Capacity forecasting models
  • Collaboration with engineering teams

Nice-to-have

  • Experience with HPC environments
  • Familiarity with observability platforms
  • Workload performance modeling
  • Process improvement using data
  • Dashboard and report communication
  • Adaptability in dynamic environments

Key Requirements

  • MS or BS in Computer Science or related field
  • 8+ years experience in data science or machine learning
  • Experience with large-scale distributed systems data
  • Experience with exploratory data analysis and model validation
  • Ability to lead analytical projects
  • Experience communicating data-driven recommendations

Work Rights

Not specified

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