Data Scientist, Algorithms - Growth Products

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.

Not sure what skills you will need for this opportunity Simply read the full description below to get a complete picture of candidate requirements.

Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse.

They cut across optimization, prediction, modeling, inference, transportation, and mapping. We're looking for someone who is passionate about solving mathematical problems with data, and are excited about working in a fast-paced, innovative and collegial environment.

As a Data Scientist on the Growth team, you will be working to grow Lyft's user base (drivers and riders) in dynamic marketplace conditions through experimentation, modeling, causal inference, and optimization.

Responsibilities :

• Partner with other scientists, engineers, product managers, and marketers to frame problems mathematically and within the business context
• Perform exploratory data analysis to gain a deeper understanding of problems
• Develop and fit statistical, machine learning, or optimization models
• Write production model code; collaborate with Software Engineers to implement algorithms in production
• Design and implement both simulated and live experiments
• Analyze experimental and observational data; communicate findings; facilitate launch decisions

Experience :

• M.S. or Ph.D. in Statistics, Operations Research, Mathematics, Computer Science, or other quantitative fields or related work experience
• 0-3+ years of professional experience for PhDs or 3-5+ years for Master’s in a data scientist role
• Passion for solving unstructured and non-standard mathematical problems
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Proficiency with Python and working in a production coding environment
• Proven experience with building and evaluating machine learning models
• Ability to collaborate and communicate with others to solve a problem
• Strong oral and written communication skills, and ability to collaborate with cross-functional partners

Benefits

• 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.

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. #Hybrid

The expected base pay range for this position in the San Francisco area is $128,000- $155,000. 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.

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