At Lyft, our purpose is to serve and connect. As a Data Scientist on the Mapping team, you will collaborate with our world class team of scientists, engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our geospatial, behavioural and mobility data, and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers.

Data Science is at the heart of Lyft’s products and decision‑making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. The Mapping team serves models and systems that determine the most efficient routes, fastest travel estimates and process real‑time map data signals to detect traffic, closures and slowdowns.

This will involve identifying and scoping opportunities, recommending technical solutions, designing experiments, and measuring the impact of new features. You will help us solve some of the most impactful problems in Mapping, including: How do we keep our travel estimation promises to our riders and drivers? Own the complete lifecycle of algorithmic solutions from problem formulation, data exploration, and feature engineering to deployment, monitoring, and iteration Prioritize and lead deep dives into our data to uncover new product and business opportunities Partner closely with Engineering to build and scale production‑grade ML systems, real‑time inference services, batch pipelines, and feature stores Design, implement, and analyze different types of experiments,



and facilitate and foster data‑driven and informed decision making and prioritization Drive scientific excellence by introducing modern techniques in ML, optimization, reinforcement learning, or graph‑based methods to unlock new product capabilities Translate complex business challenges into concrete algorithmic solutions in close collaboration with Product, Engineering, Operations, and Science teams Advanced degree in a quantitative field such as statistics, physics, economics, operations research, neuroscience, or engineering, or relevant work experience 3+ years hands‑on experience in a data science or machine learning role working with production machine learning models and optimization systems Experience independently driving multi‑project algorithmic scopes and navigating technical ambiguity from ideation to delivery Experience with machine learning models in production, making practical tradeoffs among algorithm sophistication, compute complexity, maintainability, and extensibility in production environments Working knowledge of modern machine learning frameworks and distributed computing systems, including PyTorch, TensorFlow, Ray, Spark, etc.

Extended health and dental coverage options,



along with life insurance and disability perks 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 believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy.

Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. 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. The expected base pay range for this position in the Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits.

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

📌 Data Scientist - Data Science - F/H (Toronto)
🏢 Socket.dev
📍 Toronto