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Uber Applied Scientist II Capacity & Efficiency Engineering 
United States, West Virginia 
999733864

22.11.2024

What you will do

  • Develop forecasting models and iterate on model refinement to minimize forecasting errors by developing a deeper understanding of how critical Uber infrastructure components scale
  • Derive insights from data to identify opportunities for efficiency and resource consumption reduction across the Uber infrastructure
  • Use statistical modeling techniques to develop northstar metrics and KPIs to help provide a more rigorous data-driven approach to manage Uber infrastructure
  • Develop simulation models for the Uber infrastructure to improve our understanding of the various cost drivers and how to best control them, while managing risk, reliability and availability
  • Conduct ad-hoc analysis, reporting, and build visualizations to communicate findings to Engineering Leadership
  • Present findings to senior leadership to drive business decisions

Basic Qualifications

  • 3+ years of working experience as an applied scientist in the tech industry
  • Ph.D. or M.S. degree in Statistics, Economics, Mathematics, Machine Learning, Operations Research, or other quantitative fields, or equivalent industry experience
  • Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics
  • Advanced knowledge and experience in time-series forecasting, anomaly detection and building ML models in production
  • Ability to use Python and Apache Spark to work efficiently at scale with large data sets
  • Proficiency in libraries, languages, technologies and tools like R, SQL, pandas, numpy, pyspark

Preferred Qualifications

  • Experience in algorithm development and prototyping.
  • Exposure to the infrastructure domain, particularly capacity engineering
  • Exposure to financial analysis
  • Exposure to large scale simulations

* Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to .