Data Scientist, Decisions - Passenger

Data Scientist, Decisions - Rider

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

Data Science lies at the core of Lyft’s products and decision-making process. As a member of the Rider Science team, you would operate in a dynamic environment, where we value quick progress to build the world’s best transportation. Data Scientists tackle a variety of issues, from shaping vital business decisions to creating algorithms that support both our internal and external products. We are looking for passionate, driven Data Scientists ready to address some of the most challenging and impactful problems in ridesharing.

As a Data Scientist, Decisions in the Rider team, you will apply data and rigorous analytic thinking to shape our rider app and make business decisions with our customers’ best interests in mind. You will identify and define opportunities, set priorities, propose technical solutions, design experiments, and measure their impact. You will provide a quantitative perspective to decision-making in collaboration with product, design, engineering, business, and operations stakeholders within the organization.

Responsibilities:

• Use data and analytic frameworks to uncover growth and efficiency opportunities
• Collaborate with product managers, engineers, marketers, designers, and operators to translate data insights into decisions and actions
• Design and analyze online experiments; convey results and make decisions about launching
• Create analytic frameworks to monitor business and product performance
• Establish metrics to measure the health of our products, as well as rider and driver experience

Experience:

• Degree in a quantitative field such as statistics, economics, applied mathematics, operations research or engineering (advanced degrees preferred), or relevant work experience
• 3+ years of industry experience in a data science or analytics role
• Proficiency in SQL - able to construct structured and efficient queries on large data sets
• Experience in programming, particularly with data science and visualization libraries in Python or R is beneficial
• Experience in online experimentation and statistical analysis
• Strong verbal and written communication skills, and the ability to collaborate with and influence cross-functional partners

Benefits:

• Excellent medical, dental, and vision insurance options
• Mental health benefits
• Family building benefits
• In addition to 12 observed holidays, salaried team members receive unlimited paid time off, hourly team members enjoy 15 days paid time off
• 401(k) plan to help plan for your future
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Pre-tax commuting benefits
• Lyft Pink - An exclusive opportunity for Lyft team members 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 regard 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 in a manner consistent with applicable federal, state and local law.

Starting in September 2023, this role will be performed from the office on a hybrid schedule — Team Members will be expected to work from the office on Mondays, Thursdays, and a team-specific third day. Additionally, hybrid roles offer the flexibility to work remotely for up to 4 weeks per year.

The anticipated salary range for this position in the US is $139,500-$155,000. Salary ranges are contingent on various factors including qualifications, experience, and geographic location. The range does not include potential equity offering, bonus, or benefits. Your recruiter can provide further details on the range particular to your work location and other factors during the hiring process.