Staff Scientist, Rider Booking Experience

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

This role focuses on building and evaluating AI booking agents and related ML systems for Uber's core mobility business. It involves designing experiments, developing models, and analyzing user behavior to improve the rider experience and drive growth. The role also includes shaping strategic vision, establishing metrics, and leading cross-functional initiatives.

What you'd actually do

  1. Shape the vision for the mobility booking experience and translate the strategy into measurable goals, robust models, and scalable systems.
  2. Propose and defend data-driven hypotheses in senior and executive reviews; shape long-term product direction with clear narratives and analysis.
  3. Design and scale advanced machine learning and optimization systems to power steps in the booking flow.
  4. Establish key success metrics and measurement frameworks for features and launches.
  5. Incubate 0-to-1 solutions to evaluate and iterate on emerging AI user experiences.

Skills

Required

  • Ph.D. or equivalent experience in a quantitative field such as Economics, Statistics, Machine Learning, or Applied Mathematics
  • Minimum 4 years of industry experience in Data Science, Applied Science, or related roles
  • Deep expertise in SQL, Python, and statistical analysis
  • Advanced knowledge of experimentation and causal inference methodologies
  • Experience presenting to and influencing senior leadership and executives

Nice to have

  • Minimum 7 years experience in fast-paced tech or marketplace environments
  • experience in AV mobility or delivery domains is a plus
  • Proven experience building and deploying ML or optimization models in production
  • Demonstrated leadership of large-scale, cross-functional technical initiatives
  • Entrepreneurial experience launching new product lines, systems, or 0-to-1 initiatives
  • Strong product and systems thinking, comfortable making trade-offs between ideal science and product reality
  • Strong communication, storytelling, and influencing skills

What the JD emphasized

  • evaluate AI booking agents
  • emerging AI user experiences
  • building and deploying ML or optimization models in production

Other signals

  • evaluating AI booking agents
  • building targeting models for messaging in the app
  • running large scale experiments to improve the UX
  • design and scale advanced machine learning and optimization systems to power steps in the booking flow
  • Incubate 0-to-1 solutions to evaluate and iterate on emerging AI user experiences