Data Science, Metrics

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 and analytics are at the heart of Lyft's products and decision-making. The Metrics team sits in the Central Market Management organization and owns the business metrics that leaders use to run the marketplace. We define these metrics, build and manage the tools and dashboards that make them reliable and easy to access, and drive consistent, standardized definitions across the organization.

We are looking for a Data Scientist to join the Metrics team and help shape Lyft's products and decision-making. You will own a domain within the team's surface area, building and maintaining the data and metrics that leaders and partner teams rely on, with significant executive exposure along the way. We want an intellectually curious person with strong attention to detail, a track record of analytical problem-solving, and skilled communication.

You will report to a Data Science Manager.

• →Own one or more domain datasets end-to-end, from source data through to the metrics that consumers rely on
• →Build and maintain the processing logic and pipelines that turn raw inputs into trusted, analysis-ready data
• →Own the business metrics derived from that data, developing the deep understanding of the source needed to build each metric correctly
• →Ensure the data is accurate, consistent, and reliable, with quality checks that catch problems before consumers see them
• →Deliver data and metrics to stakeholders in a usable form, and support them as they integrate it into their decisions
• →Partner with product managers, engineers, and operators to translate the data into decisions and action
• →Communicate findings to stakeholders in a clear and concise manner

• Degree in a quantitative field such as statistics, economics, applied math, operations research, or engineering (advanced degrees preferred), or relevant work experience
• 3+ years of industry experience in a data science or analytics role
• Proficiency in SQL, with the ability to write structured and efficient queries on large datasets
• Programming experience, especially with data science and visualization libraries in Python or R
• Strong oral and written communication skills, and the ability to collaborate with and influence cross-functional partners