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Uber Staff Scientist Driver Incentives 
United States, West Virginia 
242429580

Yesterday

What You'll Do

  • Design, build, and analyze statistical, optimization, and machine learning models for a range of applications in incentives and supply positioning, such as personalized offers for drivers, dynamic earning opportunities, and strategic positioning of supply (drivers, AVs, fleets).
  • Lead the design, execution, and interpretation of large-scale experiments to test new incentive strategies, supply positioning algorithms, and product features, drawing detailed and actionable conclusions.
  • Conduct deep-dive data analyses to understand supply behavior and patterns, identify opportunities for improving incentive effectiveness and supply utilization, and assess the impact of current programs.
  • Develop frameworks to optimize driver incentive products by managing trade-offs between driver engagement, incentive spend effectiveness, and overall marketplace efficiency.
  • Collaborate with cross-functional teams including product managers, engineers, operations specialists, and other data scientists to define the product roadmap, develop new features, and drive system development from ideation to production.
  • Present findings, insights, and recommendations to senior management and business leaders to inform strategic decisions.
  • Provide technical mentorship and thought leadership to the team, championing best practices in data science, statistical analysis, and machine learning.
  • Stay abreast of the latest advancements in relevant fields and propose new methodologies and approaches to solve key business problems.

Basic Qualifications

  • Ph.D., or M.S. in Statistics, Economics, Machine Learning, Operations Research, Computer Science, or another quantitative field.
  • Minimum 5 years of industry experience as an Applied Scientist, Data Scientist, or in a similar quantitative role.
  • Strong knowledge of the mathematical foundations of statistics, machine learning, optimization, and economics.
  • Proven experience in experimental design (e.g., A/B testing) and causal inference.
  • Proficiency in using Python or R for data analysis, modeling, and algorithm prototyping at scale with large datasets.
  • Experience with exploratory data analysis, statistical analysis and testing, and model development.

Preferred Qualifications

  • 6+ years of industry experience as an Applied Scientist, Data Scientist, or in a similar quantitative role.
  • Ph.D. in a relevant quantitative field.
  • Deep expertise in areas such as marketplace experimentation, causal inference, ML, or optimization, particularly in the context of multi-sided platforms, incentive systems, or logistics.
  • Proficiency in SQL.
  • Experience in algorithm development and prototyping, and with productionizing algorithms for real-time systems.
  • Demonstrated ability to translate complex analytical results into clear, actionable insights and influence product and business strategy.
  • Excellent communication and presentation skills, with the ability to articulate technical concepts to diverse audiences, including senior leadership.
  • Experience leading technical projects and influencing the scope and direction of research.
  • Familiarity with big data technologies (e.g., Spark, Hive, HDFS).
  • Strong business acumen and the ability to shape vague questions into well-defined analytical problems and success metrics.

For New York, NY-based roles: The base salary range for this role is USD$212,000 per year - USD$235,500 per year.

For San Francisco, CA-based roles: The base salary range for this role is USD$212,000 per year - USD$235,500 per year.

For Seattle, WA-based roles: The base salary range for this role is USD$212,000 per year - USD$235,500 per year.

For Sunnyvale, CA-based roles: The base salary range for this role is USD$212,000 per year - USD$235,500 per year.