Data Analyst - Physical Infrastructure

xAI xAI · AI Frontier · Memphis, TN · Data Center

This role focuses on analyzing data related to physical infrastructure for datacenters and power generation facilities, with the goal of optimizing these facilities for AI supercomputing. Responsibilities include data collection, cleaning, analysis, forecasting, dashboard development, and identifying optimization opportunities. Basic qualifications include experience in data analysis, SQL, Python/R, and BI tools. Preferred skills include background in energy, datacenters, or industrial facilities, and knowledge of power systems and cooling metrics.

What you'd actually do

  1. Collect, clean, integrate, and analyze high-volume power, cooling, and energy usage data from datacenter facilities and power plants
  2. Build and refine forecasting models for electricity, water, and other utility consumption to support budgeting, planning, and procurement
  3. Design, develop, and maintain interactive business intelligence dashboards and reports (using tools such as Seeq, Tableau, Power BI, Looker, or similar)
  4. Identify trends, anomalies, inefficiencies, and optimization opportunities in power distribution and cooling systems
  5. Partner with mechanical, electrical, and facilities engineering teams to translate analytical findings into engineering and operational improvements

Skills

Required

  • 4+ years of professional experience in data analysis, business intelligence, or analytics engineering
  • Strong SQL skills
  • Proficiency in Python (pandas, scikit-learn, or similar) or R for data analysis and modeling
  • Hands-on experience building dashboards and visualizations with Tableau, Power BI, Looker, or equivalent
  • Solid foundation in statistics, time-series analysis, and forecasting techniques
  • Experience working with large datasets and building scalable reporting solutions
  • Excellent written and verbal communication skills

Nice to have

  • Background in energy, utilities, datacenters, critical infrastructure, or industrial facilities
  • Familiarity with SCADA systems, building management systems (BMS), or IoT sensor data
  • Experience with cloud data platforms (Snowflake, BigQuery, AWS/GCP/Azure data services)
  • Knowledge of power systems, HVAC/cooling efficiency metrics (PUE, WUE, etc.), or energy modeling
  • Advanced degree in Data Science, Statistics, Engineering, Operations Research, or related quantitative field

What the JD emphasized

  • physical infrastructure for AI supercomputing
  • optimize our rapidly expanding physical infrastructure