At Lyft, community is what we are and it’s what we do. It’s what makes us different. To create the best rides for all, we start in our own community by creating an open, inclusive, and diverse organization where all team members are recognized for what they bring.

Lyft’s Research Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We are hiring motivated experts in each of these fields. We're looking for someone who is passionate about solving mathematical problems with data, and are excited about working in a fast-paced, innovative and collegial environment.

The Forecasting team builds short-term (real-time) and long-term forecasts of market signals to power business planning at multiple levels including engagement budget planning, supply positioning, pricing, support staffing, etc. We are looking for scientists to work on near-term forecasts at a high spatiotemporal resolution, using both endogenous and exogenous/unstructured features such as event data (e.g. occurrences of concerts, games) and weather. 

You will report into a Science Manager.

Responsibilities:

• Partner with other Scientists, Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context.
• Perform exploratory data analysis to gain a deeper understanding of the problem
• Build machine learning and statistical prediction models on spatiotemporal data of varying resolutions and hierarchical structures
• Write production modeling code; collaborate with Software Engineers to implement algorithms in production
• Gather customer requirements and define observable metrics of success
• Analyze experimental and observational data; communicate findings; facilitate launch decisions

Experience:

• M.S. or Ph.D. in Statistics, Mathematics, Computer Science, or other quantitative fields
• 3+ years professional experience in building statistical and machine learning models using spatiotemporal data 
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Proficiency with Python
• Willingness to collaborate and communicate with others to solve a problem