This listing does not state pay. Across 170 open data scientist listings that state pay, the middle half runs $127,000 to $186,000 and the median is $151,500.

Listed pay is what employers advertise, not what people are paid.

Data Scientist salaries by state · Check your own pay

How AI is used in this kind of work

Among data scientists, AI is already used for a large share of the tasks. Measured exposure for data scientists: 46% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

Check how this applies to your own job

Skills this job asks for

Say which you have and which you want to build. We use it to match you to jobs like this one.

About the job

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. Data Scientists at Lyft operate in a dynamic environment, and partner closely with cross-functional teammates to tackle a variety of highly open-ended business problems to build the world’s best transportation solutions.

The Pricing team is a centerpiece of Lyft’s marketplace, determining prices for all rideshare products and supporting new initiatives, and Rider Engagement is an integral part of that. Rider Engagement manages one of the most impactful marketplace and business levers, driving both short term and long term business outcomes. The team owns the algorithms and systems behind incentive offers, budget management, operational control and real-time optimization.

We are looking for fast learning, data-driven individuals who are passionate about tackling these open-ended problems in pricing theory and making a large, positive impact in the business. In this role, you will work closely with Product, Engineering and Analytics on a cross-functional team to develop and iterate incentive levers, prototype and build end-to-end solutions that can operate at scale. In addition, you will be expected to leverage your domain knowledge and influence existing and future roadmaps to help Lyft continue to deliver a better experience for riders and drivers.

Responsibilities:

Partner with other Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context

Write production code. Collaborate with Software Engineers to implement algorithms in live systems and ensure the robustness of the systems

Develop and fit statistical, machine learning, or optimization models. Deploy production-grade models that solve business problems.

Design, implement, and analyse different types of experiments, and facilitate data-driven and informed decision making and prioritization

Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes

Perform deep dive analysis to gain a deeper understanding of the problem and uncover new product and business opportunities

Drive collaboration and coordination with cross-functional teams. Communicate findings to a broad audience consisting of Product, Engineering, and executive leadership.

Experience:

M.S. or Ph.D. in Machine Learning, Operations Research, Statistics, Computer Science or other quantitative fields

1-4+ years professional experience for PhDs or 3-5+ years for Master’s in a Data Science role in a technology company setting

Proven experience with building and evaluating optimization or 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 verbal and written communication skills, and ability to collaborate and communicate with others to solve a problem

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 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

Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

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/year. 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.