Uber - San Francisco, CA
posted about 2 months ago
This is a key role as a thought leader and key contributor to Machine Learning efforts across several key domains in Marketplace, specifically focusing on the Job-Driver Matching system, Driver offer pricing, and Driver Surge pricing. The ML models utilized in these domains encompass a variety of approaches, including causal ML models, reinforcement learning models, and forecast models. The challenges faced in these areas include data sparsity and the delay in realizing the impact of actions due to the physical nature of Uber's business. Additionally, network effects arise from the limited supply of drivers shared across riders, long-term behavioral changes within the driver community, and geographical differences in driver values and Uber's business operations. These factors contribute to a complex and open problem space within the field of machine learning, making the impact of this role extremely significant given the marketplace levers it supports. The team is composed of the Driver offer pricing, Matching, and Driver surge teams within the Uber Marketplace organization. This team is responsible for systems that make optimal decisions regarding driver pricing and job-driver matching. They work cross-functionally with various organizations at Uber, including the Earner and Rider teams, Operations, and Platforms, to ensure effective collaboration and decision-making across the board.