Staff Infrastructure Efficiency Analyst

Uber Uber · Consumer · San Francisco, CA · Data Science

This role focuses on cloud cost optimization and financial accountability within Uber's cloud environments. The analyst will use data analysis, machine learning, and engineering expertise to identify and implement optimizations, improve forecasts, and drive efficient growth. Key responsibilities include analyzing cloud consumption data, tracking savings, defining performance metrics, managing reporting, and partnering with engineering teams on resource optimization and demand planning.

What you'd actually do

  1. Translate complex cloud consumption data into actionable insights for leadership and engineering.
  2. Identify and track optimizations and realized savings.
  3. Establish key price-performance metrics and partner with engineering to implement price-performance optimizations within production scaling.
  4. Define and manage reporting of cloud consumption metrics and KPIs, ensuring transparency, accuracy, and accountability.
  5. Establish consumption anomaly detection capabilities and reporting.

Skills

Required

  • Ph.D., M.S. or Bachelor's degree in Economics, Statistics, Machine Learning, Operations Research, or other quantitative fields.
  • 7+ years of industry experience as an Applied or Data Scientist or equivalent (or 4+ years with Ph.D.).
  • 5+ years of industry experience working with Cloud, either at a hyperscaler or as a cloud customer.
  • Familiarity with cloud compute, storage, and data analytics concepts and products
  • Demonstrated experience mentoring and coaching junior analysts or peers
  • Excellent communication and collaboration skills
  • Background in at least one programming language (eg. Python, R, Java, Ruby, Scala/Spark or Perl).
  • Ability to use Python or similar technologies to work efficiently with large data sets and prototype algorithms & models.
  • Coding and SQL proficiency
  • Fluency in MS Excel/Google Sheets

Nice to have

  • Experience with cost optimization analysis & implementation, ideally for cloud spend or compute infrastructure.
  • Experience in leading key technical projects and substantially influencing the scope and output of others.
  • Thought leadership to drive cross-functional projects from concept to production.
  • Experience in contributing to performance optimization initiatives through experimentation.
  • Experience with exploratory data analysis, statistical analysis, and model development.

What the JD emphasized

  • cloud consumption data
  • engineering
  • financial optimizations
  • cloud billing data analysis
  • forecasting
  • optimization
  • efficiency

Other signals

  • cloud billing data analysis
  • forecasting
  • identification and impact analysis of engineering and financial optimizations
  • machine learning
  • engineering
  • optimize our infrastructure
  • deliver efficient growth