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Data Scientist, Decisions, Rider Experience

1 month ago


San Francisco, California, United States Lyft Full time
About the Role

At Lyft, we're committed to improving people's lives with the world's best transportation. As a Data Scientist, Decisions in the Rider team, you'll play a critical role in shaping our rider app and making business decisions that put our customers first.

You'll leverage data and rigorous, analytical thinking to identify opportunities for growth and efficiency, partner with product managers, engineers, marketers, designers, and operators to translate data insights into decisions and actions, and establish metrics that measure the health of our products and rider experience.

As a member of the Rider Science team, you'll report to a Data Science Manager and work in a dynamic environment where we embrace moving quickly to build the world's best transportation.

Responsibilities
  • Leverage data and analytic frameworks to identify opportunities for growth and efficiency
  • Partner with product managers, engineers, marketers, designers, and operators to translate data insights into decisions and actions
  • Define experimentation best practices, design and analyze online experiments; communicate results and facilitate launch decisions
  • Establish metrics that measure the health of our products and rider experience
  • Lead deep dives into rider experience and marketplace data to uncover new product and business opportunities
  • Facilitate and foster data-driven and informed decision making and prioritization
  • Present findings, recommendations, and results to senior leadership and cross-functional stakeholders
Requirements
  • Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
  • Minimum 5+ years experience in strategic data science roles in a technology company, management consulting, investment firms, or an equivalent analytical role in a high growth startup
  • Experience in leading high visibility projects and influencing others in a cross-functional team environment
  • 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 in online experimentation and statistical analysis
  • Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners
What We Offer
  • 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.

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. #Hybrid

The expected base pay range for this position in the San Francisco area 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.