At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

The core of Lyft’s business is running a balanced marketplace; ensuring there are enough drivers available to fulfill rider demand. As a member of the Central Market Management team, you will work in a dynamic environment, where we embrace moving quickly to build the world’s best transportation. Data Scientists in Central Market Management take on a variety of problems including forecasting supply & demand in the marketplace, optimizing investments over different time-scales, measuring the return-on-investment of various growth levers, and shaping strategic business decisions. Forecasting, machine learning (ML), statistical inference, and optimization technologies are critical to solving these interesting and impactful problems at Lyft. Our problems generally do not lend themselves to off-the-shelf solutions, allowing for a significant amount of creativity and first-principles mathematical reasoning.

As a Data Scientist, you’ll be hands-on with building ML models, productionalizing pipelines, and integrating their outputs within decision-making frameworks. The ideal candidate should have strong technical abilities in ML-based forecasting & optimization, and have a keen interest in rigorously applying these methods to financial and resource allocation problems. You’ll partner closely with product, engineering, and business teams to build and scale our products & systems, shape long-term strategy, and deliver business goals.

• Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context
• Build fit-for-purpose models to address business needs
• Write production model code; collaborate with Software Engineers to implement algorithms in production
• Present findings, recommendations, and results to senior leadership and cross-functional stakeholders

• M.S. or Ph.D. in Operations Research, Mathematics, Computer Science, Statistics, or other quantitative fields or related work experience
• 2+ years of hands-on experience in ML-based forecasting and optimization, and a strong interest in rigorously applying these methods to financial and resource allocation settings
• Passion for solving unstructured and non-standard mathematical problems
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Proficiency with Python, or another interpreted programming language like R or Matlab
• Strong ability to collaborate and communicate with others in a team setting

• Great medical, dental, and vision insurance options
• Mental health benefits
• Family building benefits
• In addition to 12 observed holidays, salaried team members have unlimited paid time off, hourly team members have 15 days paid time off
• 401(k) plan to help save for your future
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Pre-tax commuter benefits
• Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity/affirmative action employer committed to an inclusive and diverse workplace. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.  

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, Thursdays and a team-specific third day. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year.

The expected base pay range for this position in the San Francisco is $139,500 - $155,000.  Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.