Why Hover wants you

Hover's product suite has expanded significantly in recent years. We've launched new solutions across the Pro workflow, introduced AI-driven design visualizations, and scaled to serve homeowners, contractors, and insurance carriers. Our Product Analytics team partners closely with Product Management, Design, Engineering, and Data Science to keep product decisions grounded in solid data and a real understanding of how people use what we build.

This role owns the analytics behind our most magical product and our biggest open opportunity. Hover turns a phone scan of a house into an accurate 3D model, and that model into the measurements and estimates a contractor bids from. Homeowners look at their own home in that model, which makes it the most consumer-facing thing we build. Today, the flow from 3D model to finished estimate converts poorly, and nobody owns the analytics behind it. We know usage is low. We don't yet know where it leaks, what the real blockers are, or how success should be measured. That's what you'd figure out.

This role demands an owner mindset. You'll define the measurement framework rather than inherit one, build our experimentation practice for 3D from scratch, and work directly with senior product and engineering leaders to shape the roadmap. You'll handle a wide range of analytical needs along the way: tracking plans, dashboards, experiment design, and deep-dive product analyses.

Your background likely spans product analytics, experimentation, data science, or product strategy, and you're looking for broad scope with a short distance between your analysis and a real decision. Final leveling will be determined based on experience and alignment during the interview process.

You will contribute by

You'll own the analytical backbone of Hover's 3D and Estimates experience, embedded in the product team rather than sitting beside it. You'll scope your own questions, do the data work, and tell the story that changes what we build. Our stack is Segment, Split, dbt, and Hex, and all of it is in active development, so you'll shape it instead of inheriting it.

• Define how we measure the flow from 3D model to Estimates, find where it leaks, and make the case for the product changes that fix it
• Partner with Product Managers and Engineering Leads to define success metrics, design experiments, and evaluate product performance
• Lead experiment design and analysis for A/B tests and quasi-experimental studies, and write the playbook that sets how we design, run, and read tests across the company
• Evaluate the new 3D experiences arriving as our Inspections product begins to inform the model, including damage assessment, and think through how they interact at a systems level
• Improve the telemetry we depend on in Segment, and run cleaner experiments through Split
• Build frameworks that help stakeholders align around insights and prioritize the work that moves user and business outcomes
• Raise the bar for data-driven decisions across the product organization by extending our semantic layer in dbt and Hex Context Guides, improving self-serve analytics, and mentoring peers

Your background includes

• 7+ years in product analytics, data science, or a related role, focused on user behavior and experimentation
• Expert-level SQL for complex extraction and analysis, with real comfort in messy, evolving data
• Hands-on ownership of experimentation, including experimentation platforms and statistical methods (A/B testing, causal inference). You choose the metrics and guardrails, read the results, and tell the team what to do next
• Strong familiarity with BI and analytics notebook environments (Hex, Mode, Tableau, Looker, or similar), and the judgment to build analysis others reuse
• Experience with modern data stacks (dbt, Snowflake, Hex) and product analytics platforms (Amplitude, Mixpanel)
• Curiosity and hands-on experience using AI to accelerate analysis, surface insights, or improve how you work
• Strong product sense, and the ability to communicate complex findings clearly to technical and non-technical audiences through clean decks, documentation, and visualizations
• A track record where your analysis changed what a team built, not only what a team knew, and a willingness to bring that perspective to cross-functional rooms rather than waiting to be asked for numbers

Nice-to-haves

• Python for analysis or automation
• Experience with Segment or another CDP, and with Split, LaunchDarkly, Statsig, or Eppo
• Consumer product experience, especially where UX decisions drove conversion
• Comfort with quasi-experimental methods where a clean A/B test isn't possible
• Exposure to 3D, spatial, or computer vision products
• Exposure to construction, home services, insurance, or another operationally complex industry

Benefits

• Compensation - Competitive salary and meaningful equity in a fast-growing company
• Healthcare - Comprehensive medical, dental, and vision coverage for you and dependents
• Paid Time Off - Unlimited and flexible vacation policy 
• Paid Family Leave - We support work/life balance and offer generous paid parental and new child bonding leave 
• Mandatory Self-Care Days - A day set aside each month to allow employees to recharge 
• Remote Wellbeing Resources - We provide recurring fitness classes, meditation/ mindfulness tools, virtual therapy, and family planning assistance 
• Learning - We encourage continued education and will help cover the cost of management training, conferences, workshops, or certifications

Hybrid roles at Hover

Hover has Hubs in San Francisco and New York City, where we expect that all employees living within a 50-mile radius of our offices will come into their local Hover office at least three times a week to build rapport and foster organic connection. At this time, Hover is not considering fully remote roles.

The US base salary range for this full-time position is $172,000-$212,000 annually. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all applicable US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

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