Data Scientist, Decisions - San Francisco, CA

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 dynam ...

Job description

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 dynamic environments, moving quickly to build the world's best transportation solutions. We tackle a wide range of challenges—from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products.

We are looking for an experienced and highly motivated Data Scientist to join the Central Market Management team and lead key initiatives that enhance the quality of our overall decision-making. You'll work cross functionally with other Data Scientists, Data Analysts, Product Managers, and Finance partners to make sure we are making the most financially efficient decisions to scale our business. You will identify gaps in our operational processes and measurements, and work to create strategies, frameworks, and models to help address them and deliver impact. 

Responsibilities

• Leverage data and analytical frameworks to identify opportunities for improving operational efficiency
• Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty
• Deliver integrated, high-quality analytical outputs spanning multiple projects while navigating ambiguity, cross-team dependencies, and open-ended scope
• Define and implement a robust attribution framework to evaluate the performance of high-stakes decisions
• Act as a technical lead, guiding other Data Scientists and fostering a culture of analytical excellence
• Write efficient, clean, production-level code (Python, SQL), ensuring reproducibility, documentation, and long-term maintainability of analytical assets
• Be proactive in pursuing opportunities and have a true ownership mindset to get things done
• Contribute to the Science community (hiring, onboarding, documentation, knowledge-sharing, tooling improvements), helping make Decision Science at Lyft more effective and scalable

Experience

• Bachelor's, Master's, or PhD in a quantitative field such as Statistics, Economics, Computer Science, Engineering, Applied Mathematics, or related discipline; or equivalent practical experience.
• 3+ years of industry experience in decision science, analytics, statistics, or data science, with a track record of influencing strategy and business outcomes through data.
• Demonstrated ability to own multi-project analytical scopes with ambiguous problem definitions and cross-functional integration.
• Expertise in metric design, diagnostic analysis, forecasting, behavioral analytics, decision frameworks and measurement strategy is a plus.
• Proficiency in SQL, Python, and tools for data manipulation, statistical modeling, visualization, and reproducible pipelines.
• Ability to translate analytical insights into clear, actionable recommendations for both technical and executive audiences.
• Proven success driving alignment and influencing cross-functional teams in fast-paced, ambiguous, high-stakes environments.
• Strong communication, critical thinking, and prioritization skills, including the ability to challenge assumptions, propose alternatives, and balance short-term vs. long-term tradeoffs.
• Experience working with financial data is a plus.
• Experience building and scaling monitoring systems and business health dashboards that identify anomalies, trends, and opportunities.

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, 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.