Uber Marketplace's Rider Pricing & Incentives team aims to foster growth and improve marketplace efficiency through pricing and promotion optimizations, addressing challenging marketplace problems that directly and significantly impact Uber's top-line and bottom-line.
Requirements
- Expertise in machine learning and optimization algorithms
- Experience with ML frameworks
- Experience with productionizing ML systems
- Proficiency in at least one coding languages such as Python, Go, Java and etc
- Experience in formulating and solving optimization problems
- Experience in evaluating ML models and overall system in a production environment
- Experience in designing data collection policy for ML models and policy evaluation
Responsibilities
- You will work on both ML and optimization projects to push the frontier of rider pricing/promotion efficiency and optimize the interactions with other marketplace components.
- You will end-to-end design and implement ML models and optimization algorithms
- You will drive end-to-end project executions from scoping, offline evaluation, conducting experiments, influencing launch decisions, productionization, and post-launch monitoring
- You will collaborate with cross-functional partners including product managers and scientists
Other
- 2+ years of experience in an ML/optimization role, or PhD in relevant fields (CS, OR, EE, Stats, etc.)
- Strong communication skills and can work effectively work cross-functional partners
- Strong sense of ownership to drive projects end-to-end
- Experience in causal inference and experimental design
- Experience in landing production changes into complex codebases and systems
