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.

Data Science is at the heart of Lyft’s products and decision-making.  You will work in a dynamic, impact-oriented environment, where we embrace moving quickly to build the world’s best transportation. Data Scientists take on a variety of problems ranging from shaping critical business decisions to building algorithms that power our internal and external products. We’re looking for passionate, driven Data Scientists to take on some of the most interesting and impactful problems in ridesharing.

For this role in the Lyft Business org, you will be working on one of the most profitable centers in our company.  We serve the transportation needs of outside enterprises ranging from medical care providers to management consultancies and rental car companies.  This role will require developing keen insights about the enterprises we do business and how best we can serve them using our unique capabilities.

Responsibilities:

• Set business metrics that measure the health of our products, as well as passenger and driver experience
• Partner with product managers, engineers, marketers, designers, and operators to translate business insights into decisions and action
• Find opportunities for growth and efficiency for Lyft
• Design and analyze product experiments; communicate results and launch decisions
• Develop analytical frameworks to monitor and visualize business and product performance
• Be a mentor to junior data scientists and a data-driven thought leader to cross-functional managers

Experience & Skills:

• Degree in a quantitative field like statistics, economics, applied math, operations research or engineering. Advanced degrees (Master’s or PhD) are preferred but not required
• 2+ years of industry experience in a product analytics-based science or stats role
• Proficiency in SQL - able to write structured and efficient queries on large data sets
• Experience in programming, especially with data science and visualization libraries in Python
• Experience with Machine Learning at a basic or higher level is desirable
• Experience in experimentation and statistical analysis
• Strong oral and written communication skills, and ability to collaborate with cross-functional partners to build the business

Benefits:

• 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 Progra

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 area is $128,000 - $150,000. 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.