At Lyft, the business and/or technical problem is to leverage data science, optimization, and inference to shape critical business decisions and develop new products for Lyft Ads and Lyft Business, ultimately serving and connecting people.
Requirements
- Proven experience with building and evaluating optimization models
- Proficiency with Python and working in a production coding environment
- Passion for solving unstructured and non-standard mathematical problems
- End-to-end experience with data, including querying, aggregation, analysis, and visualization
Responsibilities
- Drive the Science and Machine Learning roadmap of the team's problem area; leverage data and analytic frameworks to direct creations and improvements of algorithms and models underpinning the team's systems and products
- 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
- Provide coaching and technical guidance for other teammates
Other
- M.S. or Ph.D. in Machine Learning, Statistics, Computer Science, Mathematics, or other quantitative fields
- Strong verbal and written communication skills, and ability to collaborate and communicate with others to solve a problem
- Drive collaboration and coordination with cross-functional teams
- This role will be 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.
