Data Scientist
Algorithms, Telematics
Posted on 2/8/2024
Lyft

10,001+ employees

Ridesharing app
Company Overview
Lyft's mission is to improve people's lives with the world's best transportation. The company operates a mobile platform for the ridesharing of cars, bikes, and scooters and serves over a million rides per day.

Company Stage

Series I

Total Funding

$4.4B

Founded

2012

Headquarters

San Francisco, California

Growth & Insights
Headcount

6 month growth

1%

1 year growth

-1%

2 year growth

2%
Locations
Toronto, ON, Canada
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
Data Structures & Algorithms
SQL
Data Analysis
CategoriesNew
AI & Machine Learning
Data & Analytics
Requirements
  • M.S. or Ph.D. in Computer Science, Engineering, Statistics, or other quantitative fields
  • 1-2+ years of professional experience for PhDs or 2-4+ years for Master’s in a data scientist role
  • Proficiency with Python in a production environment
  • Familiar with SQL - able to write structured and efficient queries on large data sets
  • Ability to collaborate and communicate with others to solve a problem
Responsibilities
  • Partner with other scientists, engineers and product managers across the Telematics team to roadmap, develop and productionize new safety insights
  • Perform exploratory data analysis to gain a deeper understanding of problems, assess feasibility of an idea and surface new use cases for our Telematics data
  • Develop and fit statistical and machine learning models, as well as use signal processing techniques to develop insights
  • Partner with teams across Risk and other teams at Lyft to ensure successful adoption of safety insights into products
  • Effectively communicate findings and facilitate decisions along the model and product development cycles
  • Develop dashboards and processes to monitor the health of our data and insights pipelines, and mitigate disruptions to downstream consumers
Desired Qualifications
  • Passion for solving unstructured and non-standard mathematical problems
  • End-to-end experience with data, including querying, aggregation, analysis, and visualization