- Manage and improve Driver Engagement models and processes to run the marketplace more efficiently
- Partner with Product, Engineering, Data Science & Analytics, Revenue Operations and other cross-functional stakeholders to achieve business goals
- Leverage data science and analytics to understand critical business problems and recommend action plans
- Develop frameworks, roadmaps, and metrics for the team and broader organization
- Collaborate with other leaders and executives to build data-informed business strategies and roadmaps
- Degree in a quantitative field like statistics, economics, applied math, operations research or engineering. Advanced degrees are preferred
- 6+ years of hands-on technical experience in a data science role or equivalent
- Track record of working through unstructured technical problems to deliver business impact
- Skilled at running cross-functional relationships and communicating with leadership across multiple organizations
- Willingness to collaborate and communicate with others to drive cross-team and cross-organization initiatives forward
- Proficiency in SQL and Python
- 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
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Data Scientist- Central Market Mgmt, Lever Insights - San Francisco, United States - Lyft
Description
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 and analytics are at the heart of Lyft's products and decision-making. The Central Market Management team works in a dynamic environment, where we embrace moving quickly to build the world's best transportation.
Within Central Market Management, Data Scientists on the Decision & Insights team take on a variety of problems ranging from long term business strategic decisions to weekly agile marketplace operations. We're looking for a passionate Data Scientist to take on some of the most interesting and impactful problems in ridesharing. You will work closely on Driver Engagement initiatives to help run the marketplace more efficiently. This is fundamental to the Lyft marketplace as these Driver Engagement initiatives help us communicate with the drivers, improve their experience and balance driver supply with ride demand. The ideal candidate has deep technical expertise, exceptional problem solving skills and is comfortable working with a highly cross functional team.
Responsibilities
Experience
Benefits:
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 $144,000 - $180,000. 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.