Analytics Lead, 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.

As an Analytics IC on the Metrics Team, you will own how key business metrics are defined, governed, and represented across our data products. You will ensure that metrics are clearly defined, consistently applied, and trusted across multiple data sources.

Working closely with Data Scientists who build and maintain domain datasets, you will focus on the integrity and usability of the data itself, establishing canonical metric definitions, maintaining consistency across reporting, and ensuring that dashboards and datasets serve as reliable sources of truth. This role is critical to ensuring that teams across the organization operate from a shared and accurate understanding of the business.

• →Own canonical definitions of key business metrics across internal and external data sources
• →Evolve metric definitions over time and drive alignment on updates across teams
• →Ensure metrics are clearly defined, consistently applied, and accurately reflected in data products
• →Maintain consistency and alignment of key metrics across datasets and reporting outputs
• →Identify and resolve discrepancies in metric definitions and reporting
• →Own dashboards and datasets used as sources of truth across teams and leadership
• →Ensure data products are clear, reliable, and usable for downstream consumers
• →Establish and uphold standards for metric accuracy, consistency, and governance
• →Partner with Data Scientists to ensure consistent implementation of metric logic
• →Act as a central point of coordination for metric-related questions
• →This is an IC (individual contributor) position

• 3–5+ years in data analytics, preferably in a high-growth environment
• Bachelor’s degree in a quantitative field (e.g., analytics, statistics, economics, finance, marketing)
• Strong SQL proficiency, including writing efficient queries on large datasets
• Experience working with diverse data sources and producing reliable, analysis-ready datasets
• Familiarity with ETL pipelines; Python or data science experience is a plus
• Strong attention to detail with a focus on accuracy, consistency, and preventing metric drift
• Ability to own and evolve canonical metric definitions and drive alignment across stakeholders
• Experience defining and maintaining source-of-truth metrics used in reporting and data products
• Strong analytical thinking and data intuition; able to validate outputs and identify inconsistencies
• Ability to work through ambiguity and translate loosely defined problems into clear approaches
• Strong communication skills and ability to collaborate effectively across teams