Data Science Manager, RevOps

San Francisco, CA

Full Time
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Posted 2 weeks ago

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. As a member of the Data Science team, you will work in a dynamic 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 a passionate, driven Data Scientist Manager to take on some of the most interesting and impactful problems and lead some of the best scientists in the industry.

As a leader on the Revenue Operation Science team, you’ll help develop the vision and lead execution of improving decisions we make to run our dynamic ridesharing marketplace efficiently. You’ll be managing data scientists, and also building relationships and partnering with product and operations teams. The ideal candidate can navigate complex technical topics, strategic problem solving, and team development to deliver business impact. If you’re driven, collaborative, resourceful, and can communicate complex ideas with ease, then we’d like to talk to you.

  • Lead and grow a high-performing team of data scientists
  • Work with cross-functional partners in product, engineering, design, finance, and operations to achieve business goals
  • Prioritize and lead deep dives into our data to uncover new product and business opportunities
  • Prioritize and lead development of productized models to automate operational decision-making and drive operational productivity
  • Develop analytical frameworks, roadmaps, and metrics for the team and broader organization
  • Be a thought leader and go-to expert for goals, strategy, and long-term vision
  • Facilitate data-driven and informed decision making and prioritization
  • Collaborate with other leaders and executives to build data-informed business strategy and product roadmaps
  • Serve as a champion of sound decision-making at all levels of the company
  • Degree in a quantitative field like statistics, economics, applied math, operations research or engineering (advanced degrees are preferred) or relevant work experience
  • 8+ years of hands-on technical experience in a data science role or equivalent
  • 4+ years management experience building and leading data science teams
  • Expert in experimentation, statistical modeling, causal inference, and machine learning, with a strong track record of using their deep quantitative expertise to improve business outcomes
  • Track record of guiding teams through unstructured technical problems to deliver business impact
  • Skilled at managing cross-functional relationships and communicating with leadership across multiple teams
  • Willingness to collaborate and communicate with others to drive cross-team and cross-organization initiatives forward
  • Great medical, dental, and vision insurance options
  • Mental health 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.

Job tags: Economics Engineering Finance Machine Learning Research
Job region(s): North America
Job stats:  5  0  0
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