Quantitative Analyst

4 days ago

Toronto, Ontario, Canada Lyft Full time

At Lyft, our purpose is to serve and connect. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

We're looking for a talented Data Scientist in the Pay, Integrity & Identity org who will collaborate with our world-class team of engineers, product managers, analysts, and other data scientists to help create best-in-class pay platforms, stop fraudulent actors from harming our riders & drivers, and build user trust on the Lyft platform. As a member of our team, you will run experiments (A/B tests) and develop data-driven solutions to launch new features and remove the bad actors from the Lyft platform while maintaining a positive experience for genuine users.

Responsibilities:
  • Design and analyze experiments in collaboration with other scientists, product & engineering; communicate findings to stakeholders and facilitate launch decisions.
  • Leverage advanced statistical techniques to generate quantitative insights and develop machine learning models.
  • Analyze the wide variety of signals available to identify patterns in large datasets and uncover root causes.
  • Partner with product managers, engineers, and operators to translate analytical insights into decisions and action.
  • Build data pipelines and develop analytical frameworks to monitor business and product performance.
  • Set business metrics that measure the health of our products, as well as passenger and driver experience.
Requirements:
  • Degree in a quantitative field such as statistics, economics, applied math, operations research, or engineering (advanced degrees preferred).
  • 4-6+ years of industry experience in a data science or analytical role.
  • Proficiency in SQL - able to write structured and efficient queries on large data sets.
  • Experience in programming, especially with data science and visualization libraries in Python or R.
  • Strong oral and written communication skills, and ability to collaborate with and influence cross-functional partners.

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