Senior Scientist, Rider Experience

Uber Uber · Consumer · New York, NY +2 · Data Science

This role focuses on optimizing the rider experience and driving growth in Uber's mobility business through data analysis, experimentation, and ML modeling. The scientist will develop AI systems to understand metric trends, optimize conversion funnels, and create personalized features and pricing models for riders.

What you'd actually do

  1. Refine ambiguous questions and generate new hypotheses about the product through a deep understanding of data, our customers, and our business.
  2. Design experiments and interpret the results to draw detailed and impactful conclusions that inform our decisions.
  3. Define how our teams measure success by developing metrics in close partnership with cross functional partners and creating AI systems to understand metric movements.
  4. Develop and optimize pricing models for rider loyalty offerings including ride passes.
  5. Collaborate with other Scientists and Engineers to build and improve data foundations.

Skills

Required

  • Ph.D., M.S., or Bachelors degree in Statistics, Economics, Machine Learning, Operations Research, or other quantitative fields.
  • Mininum 3 years of industry or academic experience as an Applied or Data Scientist or equivalent (with at least two of those years in industry).
  • Experience in experimental design and analysis.
  • Experience with exploratory data analysis, statistical analysis and testing, and model development.
  • Proficiency in SQL and either Python or R.

Nice to have

  • Minimum 7 years of industry experience as a Data Scientist or equivalent.
  • Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions.
  • Experience collaborating with very senior stakeholders (Director+) and generating insights to shape strategy.
  • Experience using statistical methodologies in a marketplace context.
  • Experience guiding and mentoring other Data Scientists.

What the JD emphasized

  • ML modeling
  • AI systems

Other signals

  • ML modeling
  • AI systems
  • optimize pricing models