Data Product Manager, Growth Tech

Kin Insurance
Remote (United States)Posted 1 April 2026

Job Description

Data Product Manager, Growth Tech Quick Summary Own the “why” behind conversion. Connect data across tools, surface insights, and partner with engineering to ship improvements that drive measurable growth. Who we are Kin makes life simpler, more affordable, and better for homeowners — especially in the places where climate risks, rising costs, and outdated systems make it hardest. We start with smarter homeowners insurance and expand to everything homeowners need to thrive. Using data, technology, and thoughtful human support, we’re building products that are clear, fair, and help homeowners feel confident — so homeowners aren’t left behind when they need help most. Founded in 2016, Kin is a remote-first employer with Kinfolk across more than 35 states. We serve customers in 13 states (and counting). Our disciplined growth, strong customer satisfaction, and focus on long-term sustainability fosters outstanding growth, attracts marquee investors, and earns recognition and accolades, including: -Built In Chicago’s Best Places to Work, Midsize Companies (2021-2026) -Forbes’ America’s Best Startup Employers (2021-2024) -Inc. 5000 Fastest-Growing Private Companies -Forbes’ Fintech 50 -Great Places to Work Certified (2024-2026) Most importantly, we’re building Kin to be a place where people do meaningful work with real impact — for our customers, our communities, and each other. We’re excited to tell you more about how you can contribute to our rapid growth, strong unit economics, profitability, and excellent customer ratings. To learn more about how we work and what we’re building, visit kin.com http://kin.com and see how we work. The opportunity We’re looking for a data-driven Product Manager to help us unlock growth by connecting the dots across our sales and acquisition ecosystem. This role exists to turn fragmented data into clear, actionable insight — and then translate that insight into product improvements that drive conversion. You’ll work across five core data sources — site behavior (FullStory), customer segmentation (Twilio Segment), CRM (HubSpot), call performance (Regal), and internal policy and quote data — to understand where we’re winning, where we’re losing, and why. From there, you’ll partner closely with engineering to prioritize and ship solutions that improve outcomes for both our business and our customers. Your responsibilities - Analyze and synthesize data across multiple systems to identify where leads drop off and what drives conversion - Own the identification and prioritization of high-impact growth opportunities based on data-driven insights - Define, scope, and deliver product improvements in partnership with data engineering teams - Define and manage the data layer as the single source of truth for core business metrics, enabling consistent, reliable, and self serve analysis - Establish clear definitions and alignment on key metrics across sales and operations - Improve data quality and instrumentation to ensure accurate and reliable decision-making - Translate complex, multi-source data into clear narratives and actionable recommendations - Partner cross-functionally to ensure insights lead to measurable business outcomes Success in this role In your first 6–12 months at Kin, success is less about checking boxes and more about the impact you create. You’ll use your skills and judgment to take ownership of meaningful work, improve how we operate, and help move Kin’s mission forward. Along the way, you’ll deliver outcomes that make a real difference for both Kinfolk and the homeowners we serve. By the end of your first year, you'll have established yourself as a trusted owner, showing meaningful progress across each of the areas below: - Key conversion drop-off points are clearly identified, understood, and actively being addressed through shipped improvements - High-impact product changes have been delivered that measurably improve lead-to-bind conversion rates - Stakehol ... (truncated, view full listing at source)
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