Data Analyst, SMB Self-Serve

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 Business's products and decision-making. We're looking to hire a Data Analyst to support our Self-Serve segment — the fastest-growing part of Lyft's B2B portfolio, serving small and mid-size businesses across North America. This is a hands-on role for an analyst who is energized by turning product and customer data into insights that shape strategy — and who builds those insights on a foundation others can trust and reuse.

You will be the dedicated analytical partner to the Self-Serve product team, measuring how new features — a redesigned signup experience, onboarding improvements, and lifecycle campaigns — drive customer activation and growth. You'll own the funnel from acquisition through engagement, define the metrics that matter, and deliver the insights that inform where the business invests next. The ideal candidate pairs analytical rigor with a builder's instinct — turning recurring questions into well-defined, reusable datasets instead of one-off answers — and can translate findings into a clear narrative for both technical and non-technical audiences.

Responsibilities:

• Produce high-impact analyses on Self-Serve performance that directly inform product and go-to-market strategy
• Own the Self-Serve funnel — acquisition, signup, onboarding, and engagement — building the dashboards and datasets that give the team real-time visibility into product health
• Define what the team's core metrics mean and where they live, so every dashboard, report, and tool returns the same answer to the same question
• Partner closely with Product and Engineering to validate instrumentation and surface data gaps before they distort the funnel or new features launch — catching the data quality issues that stay invisible until someone goes looking
• Turn recurring reporting into well-defined, reusable datasets, replacing one-off queries with durable foundations others can build on
• Identify recurring workflows worth automating, and help build the prompts, context, and guardrails that make AI analytics tooling reliable for the wider team
• Conduct deep-dive analyses and design experiments to establish conversion baselines, measure business impact, and uncover the “why” behind performance trends
• Partner with Data Science & Analytics, Marketing, and other cross-functional stakeholders to inform strategy and drive decisions
• Translate insights into a cohesive narrative and present technical findings to senior leadership and non-technical audiences

Experience:

• Degree (or related work experience) with a focus in analytics, statistics, economics, computer science, or other