Scientist II, Earner Experience

About the Role

The Earner org is responsible for the products and programs that make earning through the Uber marketplace a rewarding experience. As a Scientist, you will leverage your expertise in economics, operations, machine learning, and statistical modeling to improve the efficiency of our platform and help direct the development of our products.

What the Candidate Will Need / Bonus Points

• Develop creative solutions and build prototypes to business problems using algorithms based on machine learning, statistics, and optimization, and work with engineering/product to productionize those algorithms and create impact in production.
• Drive clarity and solve ambiguous, challenging business problems using data-driven approaches.
• Propose and guide the framework of data analysis to drive business insight and facilitate decisions. Establish standard methodologies for data science including modeling, coding, analytics, and experimentation.
• Leverage data to understand product performance and to identify improvement opportunities.
• Design product experiments and interpret the results to draw detailed and impactful conclusions.
• Communicate with senior management and multi-functional teams.
• Provide recommendations to assist quick product ideation and feature launch decisions.
• Build intelligent data-driven products to provide the best user experience.

• 2+ years of industry experience in data science, analytics, or a related quantitative role.
• Bachelor's degree in a quantitative field (e.g., Statistics, Economics, Computer Science, Engineering, Operations Research).
• Proficiency in SQL and a programming language like Python or R for complex data manipulation and analysis.
• Demonstrated experience designing and analyzing large-scale A/B experiments.
• Proven ability to lead projects, work autonomously, and navigate ambiguity.

• M.S. or Ph.D. in a quantitative field (e.g., Statistics, Economics, Computer Science, Engineering, Operations Research).
• Deep expertise in advanced statistical techniques, including causal inference, quasi-experimental methods, and predictive modeling.
• A track record of successfully influencing product strategy and driving business outcomes through data on a consumer app.