Uber's Delivery Marketplace needs to optimize the decision-making process for moving from point A to point B for every order, impacting UberEats and new verticals. This involves improving dispatch decisions, delivery time predictions, and pickup time estimations to solve strategically important problems and impact Uber's top and bottom lines.
Requirements
- Experience with optimization packages such as Gurobi, CPLEX, and OR Tools
- Proficiency in one or more coding languages such as Python, Java, Go, or C++
- Experience with two or three-sided marketplace design, matching/allocation, pricing optimization, etc
- 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
- Develop the objective function which balances magical user experience and economics of the business
- Improve timeliness for Uber delivery trips
- Eater and courier segmentations based delivery matching decisions
- Build new scalable algorithms for real-time delivery matching products across hundreds of global marketplaces
- Take things from mathematical formulation through to prototype and experiment
- Work with backend engineers to put your ideas into production
- Help identify new opportunities for improving our algorithms and models
Other
- PhD in relevant fields (Operations Research, Computer Science, Mathematics, Industrial Engineering, etc.) with a focus on optimization modeling
- 3+ years of industry experience developing algorithms and models for large-scale deployment
- Strong communication skills and ability to work effectively with cross-functional partners
