The Matching Segmentation team at Uber builds the systems that determine the optimal way to fulfill trips on the Mobility platform for two of the fastest growing products - Wait and Save and Priority. We work on the problems of determining which earners to send an offer to and when, the price to charge and so on! The solutions we build are critical for maintaining reliability and ensuring the trust of riders and earners alike.
Requirements
- Proficient in SQL and advanced experience (2+ years) using Python/R to able to work efficiently at scale with large datasets
- Knowledge of experimental design and analysis (A/B, Switchbacks, Synthetic Control, Diff in Diff etc)
- Experience with exploratory data analysis, statistical analysis and testing and model development
- Experience in optimization and/or algorithm development
- Experience with dashboard / data visualization tools (i.e Tableau, Mixpanel, Looker or similar)
Responsibilities
- Develop data-driven business insights and work with cross-functional stakeholders to identify opportunities and recommend prioritization of product, growth and optimization initiatives
- Design and analyze experiments, communicating results that draw detailed and actionable conclusions
- Analyze and contribute to development of optimization algos and ML models for use in mobility matching
- Collaborate with cross-functional teams such as product, engineering and operations to drive system development end-to-end from conceptualization to final product
Other
- PhD, MS, or Bachelors degree in Operations Research, Statistics, Economics or other quantitative fields
- 4+ years of industry experience as Data Scientist or equivalent
- Good communication skills across technical, non-technical and executive audiences
- Ability to work in self-guided manner
- Have a growth mindset; love solving ambiguous, ambitious and impactful problems
