The Surge team at Uber aims to maintain overall marketplace reliability by balancing supply and demand in real-time through dynamic pricing. This role is critical to Uber's mission to make transport accessible and contributes significantly to generating billions in annual gross bookings and driver earnings.
Requirements
- PhD in relevant fields (Operations Research, Industrial Engineering, Computer Science) with a focus on optimization modeling.
- 6+ years of industry experience developing algorithms and models for large-scale deployment.
- Experience with optimization packages such as Gurobi, CPLEX, and OR Tools.
- Experience with two-sided marketplace design, pricing optimization, matching/allocation, etc...
- Proficiency in one or more coding languages such as Python, Java, Go, or C++.
- Familiarity with Machine Learning models, experimentation (e.g., A/B testing) and causal inference
- Experience with real-time optimization systems (optimization under tight time constraints)
Responsibilities
- You will work with a mixed team of Engineers, Operations Researchers, and Economists.
- You will build new scalable algorithms for real-time pricing of Uber's products across hundreds of global marketplaces.
- You will help set the team's technical direction and roadmap.
- You will communicate with leadership, identify new opportunities, and help guide the growth of more junior engineers.
Other
- Strong communication skills and ability to work effectively with cross-functional partners.
- Experience mentoring and growing junior engineers
- Experience with creating and defining technical direction and roadmaps
- Experience in 0 to 1 projects from idea/inception through to launch
