Lyft is seeking a Data Scientist with expertise in experimental design and causal inference to join the Growth team. This role is pivotal in shaping how Lyft expands its user base (drivers and riders) and involves building robust systems for measuring short- and long-term impact in a dynamic marketplace.
Requirements
- 4+ years of hands-on industry experience in causal inference or data science
- Fluency in SQL/data querying and experience with large-scale data platforms
- Proficiency with Python and working in a production coding environment
Responsibilities
- Drive the entire lifecycle of data science solutions for Growth, from defining the problem with cross-functional stakeholders to deploying production models that address key business problems
- Build statistical models/pipelines, write production code, design and implement experiments
- Perform exploratory data analysis and evaluate experiments
- Oversee growth experimentation, including process development, success criteria definition, team guidance, and the creation of new experimentation methodologies
Other
- Advanced degree in a quantitative field like statistics, economics, or mathematics; or relevant work experience
- Track record of using statistics and guiding teams through unstructured technical problems to deliver business impact
- Ability to collaborate and communicate with others to solve a problem
- Strong oral and written communication skills, and ability to collaborate with cross-functional partners
- Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays.
