Staff Data Scientist, Decisions - Partnership, Loyalty & Pay

lyftΒ· Rider Loyalty & Partnerships
Apply Now β†—
πŸ“ San Francisco, CA

About this role

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.

Β Data Science is at the heart of Lyft's products and decision-making. As a member of the Science team, you will work in a dynamic environment where we embrace moving quickly to build the world's best transportation. Data Scientists take on a variety of problems ranging from shaping critical business decisions to building algorithms that power our internal and external products.

As a Staff Data Scientist, Decisions on the Partnership, Loyalty & Pay (PLP) team within Rider, you will leverage data and apply analytical thinking and causal inference to shape our rider and partner product vision, and make business decisions that put our customers first. You will identify improvement opportunities, propose and implement technical solutions, design experiments, and measure the impact of your team's decisions. You will partner closely with product, engineering, design, research, marketing, and business development to deliver programs end-to-end. You will also collaborate and build alignment with adjacent teams across Rider, Marketplace, and Finance to balance driver, rider, and business needs.

Responsibilities:

  • Drive the data science roadmap across the Partnership, Loyalty, and Pay teams. Be a primary participant in defining team goals and setting the priorities of projects for the team to address
  • Partner with org leads in product, engineering, UX research, design, marketing, and business development to initiate, design, develop, and scale zero-to-one programs and drive business strategy through data-centric recommendations
  • Define and maintain key objectives and metrics to align with the overarching goals of Rider, Marketplace, and Lyft - including incrementality measurement for partnerships, retention impact of loyalty programs, and health of Pay products
  • Apply modeling, advanced analytics, experimentation, and causal inference techniques (e.g., A/B testing, difference-in-differences, synthetic control, quasi-experimental methods) to drive decision-making at Lyft
  • Drive cross-org impact and alignment, shaping product and business strategy through data-centric presentations to VP and C-level stakeholders
  • Advise teams on best practices. Be a thought leader and go-to expert on measurement, incrementality, and causal inference for PLP stakeholders and dependency teams
  • Provide technical guidance and mentorship to junior and mid-level team members on solution design and implementation; lead code reviews and elevate team-wide technical standards

Experience:

  • Degree in a quantitative field (e.g., Stats, Econ, Math, CS) at the Master's or PhD level, or equivalent professional expertise in high-impact environments
  • 6+ years of professional experience in data science, with a history of implementing causal models that result in tangible business value
  • Subject matter expertise in the realms of causal inference, machine learning, and experimental design
  • Sharp product sense and practical experience utilizing various causal methodologies
  • Technical mastery of Python and SQL for data analysis and modeling
  • Experience crafting sophisticated measurement frameworks, including counterfactual analysis and advanced experimentation to determine true incrementality
  • Capability to unite cross-org partners, influence technical systems, and challenge existing scientific premises to steer product vision
  • Strong communication skills to explain complex scientific results and the balance between velocity and rigor to executives and peers
  • Proven track record of managing ambiguous problem spaces and converting broad business needs into structured scientific roadmaps
  • Dedication to mentoring fellow scientists, raising the bar for technical excellence, and setting standards for modeling and reasoning

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 β€” 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 $176,000 - $220,000, 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.

Frequently Asked Questions

Is the salary disclosed for the Staff Data Scientist, Decisions - Partnership, Loyalty & Pay position at lyft?
The salary for this Staff Data Scientist, Decisions - Partnership, Loyalty & Pay role at lyft is not publicly listed. Click "Apply Now" to learn more about the compensation package on their official careers page.
Where is the Staff Data Scientist, Decisions - Partnership, Loyalty & Pay position at lyft located?
This Staff Data Scientist, Decisions - Partnership, Loyalty & Pay role at lyft is based in San Francisco, CA. The position is listed as on-site or hybrid. Check the full job description or apply directly to confirm the work arrangement.
Which team or department does the Staff Data Scientist, Decisions - Partnership, Loyalty & Pay at lyft belong to?
This Staff Data Scientist, Decisions - Partnership, Loyalty & Pay position is part of the Rider Loyalty & Partnerships department at lyft. See the full job description for more information about the team structure and responsibilities.
How do I apply for the Staff Data Scientist, Decisions - Partnership, Loyalty & Pay position at lyft?
Click the "Apply Now" button on this page. You will be redirected to lyft's official application portal hosted on greenhouse where you can submit your application directly.
When was the Staff Data Scientist, Decisions - Partnership, Loyalty & Pay job at lyft posted?
This Staff Data Scientist, Decisions - Partnership, Loyalty & Pay position at lyft was posted on Jun 1, 2026. Apply as soon as possible β€” early applications are often reviewed first.
Staff Data Scientist, Decisions - Partnership, Loyalty & Pay
lyft
Apply for this role β†—

You'll be redirected to lyft's official application page on Greenhouse.