About the Role

This is a high-impact role for an analyst who wants to own the data behind a core part of our Consumer business and use it to change what gets built. You'll partner directly with product, design, and engineering to drive how we grow the direct-to-consumer funnel — from the moment someone lands on the site, through quote and approval, to activating their policy.

It starts with a real understanding of our customers, our funnel, and the levers that move conversion and retention. That understanding is what makes your analysis worth acting on. You use it to find the highest-leverage questions, spot opportunities the team hasn't seen yet, and bring recommendations that change roadmap decisions rather than just describe what happened.

The AI infrastructure we've built changes what this role looks like day to day. Mechanical analysis is faster than it has ever been, which frees you to spend your time on the parts that need judgment: framing the right question, validating what the tools produce, and drawing the conclusion the business should act on. We're further along on this than most companies, and we're still writing the playbook — you'll help shape it.

You go deep in analytics and experimentation on your product area, and AI gives you the reach to cover more ground than a traditional analyst.

Duties and Responsibilities:

• Own the analytics for your product area. You partner with PMs across the Consumer funnel — landing page, quote flow, onboarding, approval, and activation — to define success metrics, find where users drop off, and make sure decisions are grounded in data. PMs make different calls because you're in the room.
• Be accountable for outcomes, not output. You're measured on the business impact of the decisions your analysis influences — conversion, approval rate, activation, retention — not the number of analyses you produce. You connect findings across experiments and cohorts to surface patterns a single analysis would miss.
• Own experimentation for your area. Design, instrument, and interpret A/B and multivariate tests — from CTA and quote-flow changes to eligibility and onboarding — with the statistical rigor to separate real lift from noise, and help raise the quality and speed of how the team runs experiments.
• Build deep customer and funnel understanding. Develop a rich picture of how different segments behave — return visitors, demographic cohorts, traffic sources — and turn it into product recommendations that improve conversion for each group.
• Own the quality of AI-assisted analysis. Our tools pull data, read configs, and draft analysis. You use them to move faster, and you own validating and sharpening what they produce. Human judgment over AI output, always.
• Make insights self-serve. Build dashboards and frameworks that let PMs and leaders answer their own questions, and communicate findings in clear narratives that drive alignment and action, including with senior stakeholders.

Qualifications and Skills:

• 7+ years in product analytics, growth analytics, or data science, with real impact in high-growth, consumer-facing environments.
• A track record of changing what a product team built or prioritized — not just reporting on what shipped.
• You don't wait for a fully specified ask. You see the gap, frame the question, build the answer, and land it with the right audience.
• Expert SQL, and fluency with a modern analytics stack — Snowflake and a product analytics tool like Amplitude. Python (or R) and dbt are a plus.
• Deep experience designing and interpreting experiments and applying statistical rigor — regression, confidence intervals, hypothesis testing.
• Daily use of AI tools in your analytics workflow, with a clear-eyed sense of where they accelerate the work, where they get it wrong, and where your own judgment is non-negotiable.
• Strong communication and storytelling — able to turn complex analysis into clear, strategic narratives for PMs, engineers, and executives.

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