Senior Data Scientist, Autonomous Vehicles

The future of Lyft is a hybrid network, where autonomous vehicles and human drivers serve riders side by side on one platform. That future has already started. In September 2026, Lyft riders in Nashville were matched with Waymo autonomous vehicles on the Lyft app for the first time, a milestone years in the making. Through Flexdrive, Lyft manages the depots, charging and maintenance that keep autonomous fleets on the road. Our partnerships now span Waymo in Nashville, May Mobility in Atlanta and Baidu in Europe, with more on the way.

We are early, and the playbook for running a hybrid marketplace at scale hasn't been written yet. You will help write it.

The Global Growth organization is charting the future of Lyft's growth beyond North American rideshare's core products. This includes our premium Luxury modes and Livery drivers, building a unified Lyft presence internationally, and bringing Autonomous Vehicles (AVs) to riders domestically and abroad. As the Staff Data Scientist for AV, you will be the science leader for one of the most strategic bets at the company. You will set the vision for how we measure, optimize and grow autonomous rides on Lyft, and you will shape the strategy behind which partners we work with, which markets we enter and which products we build to win.

This is a high-visibility role with direct exposure to Lyft's executive team and to our AV partners. You will work closely with engineering, product, operations, policy and partnership leaders, act as the bridge to our central marketplace science teams, and represent Lyft science in working sessions with partner teams. You will also have the opportunity to grow and define the AV science function as it scales.

The ideal candidate is a thought leader who pairs deep technical rigor with strong business judgment. You are as comfortable designing an experiment or building a causal model as you are walking a senior leader through a recommendation. In this role, you will help us tackle problems such as:

• Hybrid matching: When a rider requests a ride, how should the marketplace decide between an AV and a human driver, and how does that choice affect wait times, AV utilization and driver earnings?
• Incrementality: What is the true incremental value of an AV ride to Lyft, beyond the ride itself, and how do we translate partner metrics into Lyft's topline?
• Rider trust and adoption: What makes a rider choose, trust or opt out of an autonomous ride, and how should the product experience earn that trust?
• Partnership performance: What shared metrics and service quality guardrails should define success with each AV partner, and how do we use them to improve the product together?
• Expansion strategy: Which markets, partners and use cases (such as airports) should we launch next, how large is each opportunity, and what does it take to win?
• Fleet economics: How do depot, charging and maintenance decisions shape AV availability, and where does Lyft's fleet operations model create the most value?
• The global picture: How does our autonomous roadmap fit with international expansion and our premium modes?

Responsibilities:

• Set the multi-year science vision and roadmap for AV at Lyft, and align engineering, product and partnership leaders around it
• Define the metrics framework for AV success, including incrementality, service quality and rider experience, and drive it into partner reviews and executive reporting
• Design and lead experiments and causal analyses on AV products, from rider onboarding to matching to post-ride experience
• Partner with central marketplace science teams to shape matching, pricing and supply models that work for a hybrid network
• Build the market sizing and business cases that guide where Lyft launches AVs next
• Represent Lyft science with AV partners and turn joint data into product improvements
• Mentor data scientists and analysts across Global Growth and help build the AV science team

Experience:

• Advanced quantitative background: Master's or PhD in Economics, Statistics, Operations Research, Applied Math, Computer Science or a related field, or equivalent high-impact industry experience
• 7+ years in applied data science or applied science, with a track record of work that changed product direction or business strategy
• Deep, hands-on experience with causal inference and experimentation, including experiment design in two-sided marketplaces, counterfactual analysis and measuring incrementality
• Experience setting the technical direction for a product area and influencing roadmaps across multiple teams
• Experience presenting to senior executives and external partners, and turning complex analysis into clear decisions
• Strong proficiency in Python and SQL
• Nice to have: experience in autonomous vehicles, robotics, mobility, logistics or delivery; optimization or marketplace modeling; fleet operations or unit economics; international market expansion
• Skills
  • Ability to think strategically about complex, unstructured problems and turn them into a clear science roadmap
  • Ability to choose the right method for the decision, and to explain the trade-off between rigor and speed
  • Ability to break down large, messy datasets, including data shared by external partners, and synthesize inputs from multiple sources
  • Ability to craft a compelling story and concisely present recommendations to technical and non-technical audiences, including senior leadership
  • Ability to lead, influence and inspire others without formal authority in a fast-moving and ambiguous environment
  • Strong product and user experience sense, with real curiosity about how riders experience a new technology
  • Entrepreneurial self-starter who takes ownership, spots opportunities early and does what it takes to drive results

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

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 at least 3 days per week, including 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 Toronto area is CAD $136,000 - CAD $170,000, 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.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.