The Driver Incentives Science team is at the core of ensuring a healthy and efficient supply network (including drivers, AVs, and fleets) on the Uber platform. We design and build the algorithmic and analytical frameworks that power a variety of incentive and positioning products for drivers and other supply types. Our goal is to leverage data to understand driver behavior and marketplace patterns, optimize incentive strategies, and create a more rewarding experience for drivers, ultimately contributing to the overall health and growth of the Uber marketplace. As a Staff Scientist on this team, you will be a technical leader responsible for developing innovative solutions to complex problems in the driver incentives and broader supply positioning space. You will apply your expertise in economics, statistics, machine learning, and operations research to design, model, and experiment with new incentive structures and supply positioning (drivers, AVs, fleets) methods. You will collaborate closely with product, engineering, and operations teams to bring your insights and algorithms to life, directly impacting millions of drivers and the broader supply ecosystem globally. We are seeking an experienced scientist with a passion for tackling challenging problems, a curiosity for understanding complex systems, and a drive to build impactful solutions.