Senior Scientist, Rider Personalization

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

This role focuses on enhancing the Rider app's personalization AIML experience by leveraging data science and analysis to measure and optimize recommendation systems. The candidate will define and build metrics, ensure explainability and observability, design and analyze experiments, and design and build agentic AI to automate data science workflows. The goal is to improve user satisfaction and drive business growth through impactful personalization.

What you'd actually do

  1. Define, build, and visualize appropriate metrics to measure user behavior and algorithm performance.
  2. Explainability and observability: make data easily discoverable, understandable and actionable via simulation tooling, dashboards, etc.
  3. Design, implement, and analyze experiments/quasi-experiments using appropriate statistical methodologies (basic and advanced).
  4. Design and build agentic AI to automate data science workflows
  5. Evangelize proactive insights that influence product or algorithm strategy (e.g. discovering trends, anomalies, and behavior patterns in our AIML systems).

Skills

Required

  • Data science
  • Analysis
  • Metrics definition and visualization
  • Experiment design and analysis
  • Causal inference methodologies
  • Agentic AI

Nice to have

  • Causal inference modeling
  • Agentic AI for data science workflow automation

What the JD emphasized

  • agentic AI to automate data science workflows

Other signals

  • recommendation systems
  • personalization
  • agentic AI
  • metrics
  • experiments