At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
The Pricing team is a centerpiece of Lyft’s marketplace. The Pricing team owns the models and software systems that determine the final prices shown to riders. Working with our business and analytics partners, the team owns tools to ensure Lyft offers competitive prices while making efficient financial trade-offs. Rider Engagement is a fast-growing team within Pricing, focused on developing rider-facing engagement levers and optimizing allocations and decisioning systems to drive both short term and long term business outcomes.
As a Data Scientist specializing in Algorithms on the Rider Engagement team, you will develop mathematical models for core discounting systems and address diverse problems across optimization, prediction, machine learning, and inference. You will collaborate with cross-functional teammates and stakeholders to enhance algorithms, build and scale our rider engagement products and systems, and drive business growth. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions and decisioning frameworks. In this role, you will report to a Data Science Manager.
Responsibilities:- Partner with Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context
- Prioritize and lead deep dives into our data to uncover new product and business opportunities
- Be familiar with production code; collaborate with Software Engineers to implement algorithms and models in production
- Design, implement, and analyse different types of experiments, and facilitate and foster data-driven and informed decision making and prioritization
- Establish metrics that measure the health of our products, as well as rider and driver experience
- Drive collaboration and coordination with cross-functional teams
- Provide coaching and technical guidance for other teammates
- M.S. or Ph.D. in Machine Learning, Statistics, Operations Research, Computer Science, Mathematics, or other quantitative fields
- 2+ years professional experience in a technology company setting
- Proven experience with building and evaluating machine learning models
- Proficiency with Python and working in a production coding environment
- Passion for solving unstructured and non-standard mathematical problems
- End-to-end experience with data, including querying, aggregation, analysis, and visualization
- Strong oral and written communication skills, and ability to collaborate and communicate with others to solve a problem
- Great medical, dental, and vision insurance options with additional programs available when enrolled
- Mental health benefits
- Family building benefits
- Child care and pet benefits
- 401(k) plan with company match to help save for your future
- In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
- 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
- Subsidized commuter benefits
- Monthly Lyft credits and complimentary Lyft Pink membership
Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. 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, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.
Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. 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, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. 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 $128,000 - $160,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
Lyft Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Lyft and has not been reviewed or approved by Lyft.
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Healthcare Strength — Corporate materials describe comprehensive medical, dental, and vision coverage with added access to One Medical and mental-health support, indicating a solid core health offering. This breadth positions health benefits as a relative strength for full-time employees.
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Parental & Family Support — Company information highlights paid parental leave for new parents, with flexibility in how time can be taken. This signals strong family support within the corporate package.
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Leave & Time Off Breadth — U.S. salaried employees have unlimited paid time off alongside company holidays, and hourly roles receive structured PTO and sick time. These policies point to ample time-off availability compared with many roles.
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What We Do
Lyft was founded in 2012 by Logan Green and John Zimmer to improve people’s lives with the world’s best transportation, and is available to approximately 95 percent of the United States population as well as select cities in Canada. Lyft is committed to effecting positive change for our cities by offsetting carbon emissions from all rides, and by promoting transportation equity through shared rides, bikeshare systems, electric scooters, and public transit partnerships.
