UberEats seeks to enhance the Eats Feed experience by addressing consumer-focused challenges in Ranking, Personalization, and Causal Inference.
Requirements
- R or Python coding, SQL proficiency and ability to develop statistical analysis and algorithm prototyping.
- Design experiments, interpret the results to draw detailed and actionable conclusions.
- Solid theoretical and applied causal inference skills, experience applying them in a practical industry setting.
- Ability to analyze large data sets to identify behavior or system trends and synthesize them to influence product direction.
- Experience leading key technical projects and substantially influencing the scope and output of others.
Responsibilities
- Design and run experiments / causal inference studies that are used to drive product decisions.
- Define how our teams measure success, by developing metrics, in close partnership with cross functional partners.
- Develop data-driven insights and work with cross-functional partners to identify opportunities to improve the product and develop technical roadmaps.
- Collaborate with other Scientists and Engineers to build and improve data foundations.
- Refine ambiguous questions and generate new hypotheses about the product through a deep understanding of data, our customers, and our business.
Other
- Ph.D., M.S., or Bachelors degree in Statistics, Economics, Operations Research, or other quantitative fields.
- Minimum 4 years of industry experience as an Applied or Data Scientist or equivalent (2+ years if holding a Ph.D.)
- Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams.
- Track record of engaging senior leadership effectively to build understanding of and consensus for the viewpoints of the team.
- Thought leadership to drive multi-functional projects from concept to production
