Optimize Uber's Mobility business by intelligently optimizing pricing and incentives allocations globally to meet near-term business goals while simultaneously optimizing for long-term enterprise value.
Requirements
- Experience leading high-performing scientists, economists, and applied researchers in an industrial marketplace setting.
- Solid understanding of experimentation and causal inference applied at scale.
- Familiarity with machine learning algorithms, optimization, and simulation strategies.
- PhD in Statistics, Economics, Operations Research or a similar field.
- 3+ years of data-science management experience with at least 5 direct reports.
- Record of significant technical contributions in a large-scale marketplace setting.
Responsibilities
- Guide a team of applied and data scientists working on challenging problems at the interface of statistics, economics, optimization, and machine learning.
- Lead a high-performing team of scientists working to optimize Uber's Mobility business.
- Focus on applied and data science to intelligently optimize pricing and incentives allocations globally.
- Serve as a role model and leader for a broader Science organization spanning multiple subteams.
- Solid understanding of experimentation and causal inference applied at scale.
- Familiarity with machine learning algorithms, optimization, and simulation strategies.
- Record of significant technical contributions in a large-scale marketplace setting.
Other
- Collaborate closely with crossfunctional partners in engineering, product, and operations roles.
- Ability to work effectively with a broad range of stakeholders.
