manager software engineering Engineering Manager hybrid

About this role

Lyft is hiring a manager-level Engineering Manager in the software engineering function based in Toronto, Canada. The posting calls out experience with Python, SQL, Data Structures, Machine Learning.

Role
Engineering Manager
Function
software engineering
Level
manager
Track
hybrid
Employment
Full-time
Location
Toronto, Canada
Department
Core XP
AI Summary
Lead a data science team building algorithms and analytics to improve Lyft's rider app experience across conversion, personalization, and platform health. Requires deep expertise in machine learning, causal inference, experimentation, and proven track record managing product data science teams in fast-paced environments.

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Job description

from Lyft careers

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 seeking a Data Science Manager to translate data into the actionable insights and algorithms that improves Rider App experiences our rider loves. In this role, you’ll shape the vision and drive execution across conversion, personalization, and platform health, ensuring we build durable relationships with every rider. By partnering with cross-functional leaders in Pricing, Loyalty, and ML teams, you will evolve our platform for both existing riders and expanding to serve new segments (e.g., Lyft Silver, Teens).

This is a high-visibility, high-impact role with direct influence on Lyft’s ride experience across millions of riders and rides everyday. The ideal candidate will bring deep expertise in advanced analytics, machine learning, causal inference, experimentation; strong business acumen in two-sided marketplace contexts; and a proven track record of leading product data science teams in fast-paced, cross-functional environments.

This is an excerpt. Read the full job description on Lyft careers →
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