Data Scientist, Algorithms, ML - Fulfillment

Company: Lyft

Location: Toronto, Ontario

Type: Full-time

Level: mid

Posted: 2026-02-04

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.


Data Science is central to Lyft's products and decision-making. As a Data Scientist on the cross-functional team, you will work in a dynamic environment, tackling a variety of problems from shaping critical business decisions to building algorithms that power our products. We seek passionate, driven Data Scientists to address some of the most interesting and impactful problems in ridesharing.


As a Data Scientist specializing in Algorithms, you will develop mathematical models for the platform's core services, addressing diverse problems in optimization, prediction, machine learning, and inference. On the Fulfillment team, you will collaborate with cross-functional teammates and stakeholders to enhance algorithms for matching rideshare supply and demand in real time and develop product offerings to improve the experiences of Lyft Riders and Drivers.


Responsibilities:

- Drive the Science and Machine Learning roadmap of the team’s problem area, leverage data and analytic frameworks to direct creations and improvements of algorithms and models underpinning the team’s systems and products
- Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context.
- Perform exploratory data analysis to gain a deeper understanding of the problem
- Construct and fit statistical, machine learning, or optimization models
- Write production modeling code; collaborate with Software Engineers to implement algorithms in production
- Design and implement both simulated and live traffic experiments
- Analyze experimental and observational data; communicate findings; facilitate launch decisions
- Develop measurement methodologies to monitor the health of our products, as well as the impacts on user outcomes and marketplace outcomes
-...

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