Uber Staff Scientist Driver Incentives 

United States, West Virginia 

242429580

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.