Uber's business problem of optimizing revenue through pricing and incentives simulation and optimization in the marketplace
Requirements
Expertise in machine learning and optimization algorithms
Experience with ML frameworks
Proficiency in at least one coding language such as Python, Go, or Java
Experience in translating ambiguous business problems into structured, principled technical solutions
Experience in developing and deploying optimization algorithms in production
Experience in causal inference and experimental design
Experience in evaluating ML models in a production environment
Responsibilities
Leading the design and implementation of ML-driven solutions to meet business requirements
Managing end-to-end project execution, from scoping and offline evaluation to experimentation, production, and post-launch monitoring
Developing and refining ML models and optimization algorithms to improve simulation accuracy and overall performance
Collaborating with cross-functional teams, including product, operations, and science partners
Develop and implement ML and optimization solutions to enhance pricing and incentive efficiency, while optimizing interactions with other marketplace components
Other
2+ years of experience in an ML/optimization role, or a PhD in a relevant field (CS, OR, EE, Statistics, etc.)
Strong communication skills and ability to work effectively with cross-functional partners
Strong sense of ownership to drive projects end-to-end
Ability to work in San Francisco, CA or Sunnyvale, CA
Eligibility to participate in Uber's bonus program and may be offered an equity award & other types of comp
