The role focuses on rider personalization and ranking systems, implying the development and deployment of AI/ML models to improve user experience and engagement within Uber's consumer platform.

Scientist II role focused on developing and analyzing ML models and optimization algorithms for Uber's mobility matching system, involving experimental design, causal inference, and large-scale data analysis to improve trip fulfillment and ETAs.

This role focuses on analyzing data, designing experiments, and building models to optimize Uber's rider pricing and incentives algorithms and platform. It involves understanding product performance, developing new metrics, and informing strategies for marketplace efficiency and reliability.

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.

Seeking a Senior Survey Scientist to design and conduct research studies using survey and behavioral data to inform Marketing, Ops, and Product strategies. The role involves developing survey instruments, analyzing data, and providing strategic advice to stakeholders. Expertise in research design, psychometrics, and quantitative methods is required.

This role focuses on designing, executing, and analyzing experiments to understand product and tool performance, particularly in driver recruitment and fleet management. It involves deep dives into user experience, collaboration with product and engineering teams, and presenting data insights to drive decisions. The position requires a Master's degree and experience in quantitative analysis, data visualization, dashboard development, data analytics tools (R or Python), and SQL.

This role involves conducting statistical and econometric analysis on policy-related topics for Uber, partnering with regional policy teams to develop evidence-based positions and support advocacy efforts, and collaborating with Product, Legal, and Operations. The ideal candidate has a quantitative background (Economics or similar), experience with SQL, Python, or R, and strong analytical and communication skills.

This role focuses on providing strategic insights, measurement, and optimization for a large brand marketing budget. It involves designing experiments, leveraging causal inference models, and analyzing large datasets to guide marketing strategy and understand customer behavior. The ideal candidate has a strong quantitative background, expertise in experimentation and causal inference, and excellent stakeholder management skills.