Growth Engineer

The Problem36 million businesses in America need insurance—it’s not optional. 77% are underinsured. 40% have no coverage at all. The distribution system failed them: too slow, too opaque, too confusing.Over 90% of commercial insurance is still human-led. We’re building the inverse: 90%+ AI-led, pushing toward the higher 90s. Not by patching legacy workflows—by building AI that makes humans more effective, improves the customer experience, and eliminates friction at every step.We’re adding ~1,000 customers per month. We’ve grown 100x since last year. We’re looking to do even more this year—and that’s why we’re hiring.To grow that fast, we need to understand—with precision—what’s working, what’s not, and why.The ThesisThe line between “analytics” and “product” barely exists here. Your models will directly power how our agents prioritize leads, time outreach, and personalize conversations. You’ll build the intelligence that tells us how well it’s working—and ship code that directly moves revenue.The RoleYou’ll own the metrics, analytics, and experimentation infrastructure that powers growth. This isn’t “build dashboards and wait for questions.” You’ll define the KPIs that matter, instrument systems to track them, and ship code that directly moves revenue.You work across paid acquisition channels—Google Ads, Meta, TikTok—combining it with product analytics and using AI to surface insights that would take others weeks to find.What You’ll DoBuild metrics and KPI infrastructure — Define, instrument, and own the metrics that matter in real timeOwn LTV/CAC systems — Track unit economics across verticals, channels, and cohortsBuild paid channel analytics — Connect ad spend to actual revenue, not vanity metricsCreate attribution that works — Multi-touch attribution across voice, email, web, and referralUse AI for insight generation — Pattern detection, anomaly detection, automated analysisShip experimentation infrastructure — A/B testing with statistical rigorYou Might Be a Fit If…You ship code—production code, not just notebooks (Python, SQL)You’ve defined KPIs, built instrumentation, and been accountable for moving themYou’ve worked with paid acquisition data (Google Ads, Meta, TikTok)You use AI to accelerate analysis (PostHog or similar)You’ve built GTM systems: lead scoring, attribution, LTV/CAC analysisYou think in experiments and know correlation vs. causationYou’re 2-5 years into your careerRequirements2-5 years experience in analytics engineering or growth engineeringStrong Python and SQL skillsExperience with paid acquisition data and funnel analyticsAbility to ship production code, not just analysisExperience with A/B testing and experimentationBased in San Francisco or willing to relocateNice to HaveExperience with PostHog, Amplitude, or similar product analyticsBackground in lead scoring or attribution modelingPrior startup or high-growth company experienceCompensationSalary: $130,000–$190,000 + performance bonuses & equityLocation: San Francisco, in-officeBenefitsHealth, dental, and vision insuranceCommuter benefitsTeam meals and snacksThe Process15-min founder call — Alignment on mission and paceTechnical conversation — Walk us through analysis you’ve doneOn-site — Meet the team, see the dataTo ApplyData talks. Narratives walk. If you prove things instead of just believing them—send your resume and an example of analysis that drove a business decision.