mid Data Scientist ic 3+ yrs Bachelor's
$108,000 – $135,000
USD per year

About this role

Lyft is hiring a mid-level Data Scientist based in Toronto, Canada. The posting calls out experience with Python, R, SQL, TensorFlow and roughly 3+ years of relevant work. Listed education preference: a bachelor's degree or equivalent. Compensation is listed at $108,000–$135,000 per year.

Role
Data Scientist
Function
data engineering
Level
mid
Track
Individual contributor
Employment
Full-time
Location
Toronto, Canada
Experience
3+ years
Education
Bachelor's degree
Department
Mapping
AI Summary
Mid-level Data Scientist on the Mapping team who leverages spatial data to improve route recommendations and travel time estimations. Designs experiments, establishes product health metrics, and translates analytical insights into business decisions for rideshare navigation products.

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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.

As a Data Scientist on the Mapping team, you will collaborate with our world class team of 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 spatial 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. This will involve identifying and scoping opportunities, shaping priorities, 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 improve the quality of our map data in order to improve our recommendations?
  • How do we benchmark and measure the success of our services?
  • How do we validate features of the real world that affect our routing algorithms?
  • This is an excerpt. Read the full job description on Lyft careers →
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