At Lyft, the business problem is to cultivate a work environment where all team members belong and have the opportunity to thrive, and to achieve this by leveraging optimization and inference to shape critical business decisions, specifically in the Pricing team to determine the prices shown to riders.
Requirements
- Proven experience with building and evaluating optimization models
- Proficiency with Python and working in a production coding environment
- End-to-end experience with data, including querying, aggregation, analysis, and visualization
- Ph.D. in Operations Research, or other quantitative fields or related work experience
- Passion for solving unstructured and non-standard mathematical problems
Responsibilities
- Partner with Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context
- Prioritize and lead deep dives into our data to uncover new product and business opportunities
- Be familiar with production code; collaborate with Software Engineers to implement algorithms and models in production
- Design, implement, and analyse different types of experiments, and facilitate and foster data-driven and informed decision making and prioritization
- Establish metrics that measure the health of our products, as well as rider and driver experience
- Drive collaboration and coordination with cross-functional teams
- Provide coaching and technical guidance for other teammates
Other
- Ph.D. in Operations Research, or other quantitative fields or related work experience
- Strong verbal and written communication skills, and ability to collaborate and communicate with others to solve a problem
- Work in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays
- Hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year
- 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
