About the role:
Leads efforts to design and implement pricing and incentive computational algorithms to optimize between various tradeoffs, e.g., revenue and growth. Leverage a mix of optimization theory and practical experience to design algorithms that are scalable, adapt to marketplace conditions, and easy to maintain.
About the Team:
The Driver pricing and incentives team sits within the Marketplace Engineering Org within Uber. Our team's charter spans incentive optimization and dynamic trip pricing to optimize for revenue and growth for all of Uber's businesses including Eats and Rides. These teams build state of the art statistical modeling, optimization, and machine learning algorithms to drive business impact. The role will provide an opportunity to work on some of the most strategic marketplace problems at Uber scale that impacts Uber's global business in a very meaningful way.
Minimum qualifications:

• PhD or equivalent in Computer Science, Engineering, Mathematics or related field AND 5-years full-time Software Engineering work experience OR 8-years full-time Software Engineering work experience, WHICH INCLUDES 5-years total technical software engineering experience in one or more of the following areas:
  • Programming language (e.g. C, C++, Java, Python, or Go)
• Note the 5-years total of specialized software engineering experience may have been gained through education and full-time work experience, additional training, coursework, research, or similar (OR some combination of these). The years of specialized experience are not necessarily in addition to the years of Education & full-time work experience indicated.

Technical skills:
Required:

• Software implementations for computational algorithms in production

Preferred:

• Knowledge of convex and linear programming
• Network optimization
• Computational algorithms for large scale optimization problems
• experience with machine learning models