Data Scientist, Algorithms

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.

Data Science is at the heart of Lyft’s products and decision-making. We are hiring a Data Scientist - Algorithms to join the Base Earnings team. This cross-functional team is responsible for setting pay for every Lyft rideshare ride, as well as ensuring compliance with our regulatory and policy commitments regarding pay. We seek a passionate data scientist to help create and improve our production algorithms for determining driver pay.

In this role, you will leverage your data, machine learning, optimization, experimentation, and/or inference skills to refine Lyft’s pay policies. You will also support operations and continuously monitor policy performance in production. Your technical impact will contribute directly to company-level metrics, including profit, rides completed, driver sentiment, and pickup reliability.

Responsibilities:

• Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context.


• Perform exploratory data analysis to gain a deeper understanding of the problem


• Design and fit statistical, machine learning, or optimization models


• Write production modeling code; collaborate with Software Engineers to implement algorithms in production


• Design and run both simulated and live traffic experiments


• Analyze experimental and observational data; communicate findings; facilitate launch decisions

Experience:

• M.S. or Ph.D. in Statistics, Operations Research, Mathematics, Economics, Computer Science, Physics, Engineering, or a similar quantitative field


• 2+ years professional experience OR a Ph.D.




• Expertise in machine learning, optimization and/or causal inference


• Proficient at writing Python code


• End-to-end experience with data, including querying, ETL, monitoring, analysis, and visualization

Benefits:

• 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.