Staff Scientist - Competitive Intelligence

Uber Uber · Consumer · Seattle, WA +2 · Data Science

This role focuses on leveraging advanced analytical methods, including statistical modeling, causal inference, and machine learning, to derive competitive intelligence and shape business strategy. The candidate will translate complex analyses into actionable insights, collaborate with cross-functional teams, and provide technical mentorship. While the role uses ML methodologies, its primary focus is on competitive strategy and business insights rather than shipping core AI/ML products.

What you'd actually do

  1. Leverage advanced analytical methods—including statistical modeling, causal inference, funnel analysis, and deep-dive analytics—to uncover Uber’s largest opportunities in a competitive landscape and drive high-impact business decisions.
  2. Translate complex analyses into actionable insights and present findings to business leaders, executives, and cross-functional partners to shape strategy.
  3. Collaborate with Product, Operations, and Engineering teams to define and execute a roadmap of high-impact initiatives, ensuring competitive intelligence is deeply integrated into Uber’s decision-making.
  4. Provide technical mentorship and thought leadership, elevating the team’s analytical rigor and advancing best practices in statistical and ML methodologies.

Skills

Required

  • SQL
  • Python
  • R
  • Statistical modeling
  • Causal inference
  • Experimental design (A/B testing)
  • Funnel analysis
  • Deep-dive analytics
  • Communication skills
  • Technical mentorship

Nice to have

  • Competitive intelligence
  • External data analysis
  • Strategic analytics
  • Observational studies
  • Quasi-experimental methods
  • Messy, incomplete, and noisy data analysis
  • Collaboration with senior stakeholders (Director+)
  • Judgment
  • Critical thinking
  • Decision-making skills
  • Navigating ambiguity
  • Prioritization

What the JD emphasized

  • Ph.D., M.S., or Bachelor's degree in Economics, Statistics, Machine Learning, Operations Research, or a related quantitative field.
  • 6+ years of industry experience as an Applied Scientist, Data Scientist, or equivalent role.
  • Strong foundation in statistical methods and modeling, including experimental design (e.g., A/B testing) and causal inference.
  • Proven ability to extract insights from data, translate complex analyses into actionable takeaways, and drive strategic decision-making.