GTM Engineer

36 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.

This is a founding role. You'll own the insight layer behind growth from day one—shaping how marketing dollars are spent, how campaigns are optimized, and how we scale. Every model you build, every experiment you run, every insight you surface becomes company DNA. Winning in 6-12 months means measurable revenue impact AND a growth analytics engine that runs itself.

You're a commercial data scientist who sits at the intersection of marketing, analytics, and product—but make no mistake, this is a growth role, not a research role. You work closely with the Head of Marketing to answer the questions that matter: what's working, what's not, why, and what to do next.

You work directly with founders. No committee. No approval chain. You surface it, you influence it, you own the outcome.

• Own funnel analytics — Track performance from lead to conversion to revenue; define and maintain core marketing KPIs

• Drive paid acquisition decisions — Analyze channel performance across Google, Meta, and beyond; influence where the budget goes

• Build and interpret LTV/CAC models — Give the business a clear picture of unit economics and what levers to pull

• Run experiments that drive growth — Design and analyze A/B tests; turn results into decisions, not just reports

• Segment and identify what's working — Cohort analysis, customer segmentation, high-performing channel identification

• Communicate insights that move people — Translate complex analysis into clear, actionable recommendations for non-technical stakeholders

• You've worked directly with marketing or growth teams—not just supported them from afar

• You can tie data to revenue outcomes, not just report metrics

• You've influenced budget allocation, campaign strategy, or targeting decisions

• You have strong SQL and solid Python

• You've analyzed paid acquisition channels and understand attribution

• You think in first principles and move fast in high-ambiguity environments

• You're based in San Francisco or willing to relocate

• Proven experience in a growth, marketing, or revenue-focused data science role

• Strong SQL; Python preferred

• Hands-on experience with funnel analysis, attribution, segmentation, and LTV/CAC modeling

• Experience designing and analyzing A/B tests and experiments

• Exposure to paid acquisition channels (Google, Meta, etc.)

• Commercial mindset — comfort influencing decisions, not just informing them

• This is not a dashboarding, BI, or ML research role

• Experience with Google Ads, Meta Ads, or TikTok Ads

• Familiarity with PostHog, Mixpanel, or Amplitude

• Background in PLG companies, high-growth startups, or SMB-heavy environments

• Exposure to AI-assisted analytics workflows

• Salary: $130,000–$190,000 + performance bonuses & equity

• Location: San Francisco, in-office

• Health, dental, and vision insurance

• Commuter benefits

• Team meals and snacks

1. People screen — Initial fit and alignment

2. Lead screen — Skills and culture fit

3. Super day — See how you operate in real time

Data 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.