Data Product Manager
About The Position
Enable the data products behind Kin’s core insurance decisions, from pricing and underwriting to actuarial analysis and claims. Get to the real question behind each request, then partner with data engineering to build the datasets those teams rely on to decide. Kin makes life simpler, more affordable, and better for homeowners, especially in the places where climate risks, rising costs, and outdated systems make it harder. 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 14 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 (2026) Inc. 5000 Fastest-Growing Private Companies Forbes’ Fintech 50 (2023-2026) Great Places to Work Certified (May 2024-May 2027) 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 and see how we work.
Requirements
- 2 to 5 years in product management, data analytics, or an analytical role close to the insurance business
- Real business sense for how data gets used to decide, ideally from time spent as an analyst making recommendations, not only shipping features
- Advanced SQL, able to pull and join data across multiple sources on your own
- Comfort in a modern data stack such as Databricks and Looker
- The instinct to dig for the real question instead of taking the first request at face value
- Precise about definitions, since a metric that drives a pricing or claims decision has to mean one thing
- Able to use AI to raise your own throughput and prototype ideas fast
- Experience partnering with engineering to scope and ship
- Some familiarity with the insurance business, or a clear appetite to learn it fast
- Clear, concise communication with a technical audience and a business one alike
Nice To Haves
- Background in InsurTech or FinTech, especially homeowners, and comfort with concepts like loss ratio, premium, underwriting, and catastrophe risk
- Familiarity with insurance systems such as Snapsheet, Xactimate, or catastrophe modeling from RMS and Verisk
Responsibilities
- Dig past the first request to the real decision a pricing, underwriting, actuarial, or claims team is trying to make, asking why enough times to get there
- Enable the data products behind those decisions, from the datasets that feed a rate review to the views a claims team works from
- Connect data across the systems that hold it, including Snapsheet and Xactimate for claims and vendor loss modeling from RMS and Verisk, so a change in any of them is understood and handled
- Build supporting datasets proactively, ahead of the questions, so teams can dig into a metric or a problem without waiting on a new pull
- Scope and deliver data products in partnership with data engineering
- Own the data layer as the single source of truth for core insurance metrics like loss ratio and pricing accuracy, so analysis stays consistent and self serve
- Nail down what each metric means before it ships, since these numbers steer real money decisions on rate and risk selection
- Improve data quality and instrumentation so these decisions rest on numbers people trust
- Translate messy, multi source data into a clear story and a recommendation someone can act on
- Partner across pricing, actuarial, underwriting, claims, and data engineering so insight turns into decisions
Benefits
- Competitive salary and company equity through Restricted Stock Units (RSUs), granted as part of our standard compensation package and based on role and level
- 401(k) with company match up to 4% of eligible earnings
- Multiple medical plan options, plus dental and vision coverage
- Company-funded HSA contributions (based on medical plan selection)
- Company-paid life insurance and short-term disability
- A variety of supplemental benefit options, including long-term disability, critical illness, accident, legal, and pet insurance
- Access to mental health support and confidential counseling resources
- Flexible PTO for exempt employees (most employees take 15–20 days per year), plus 8 company-observed holidays
- Paid parental leave, including up to 14 weeks at 100% pay for birthing parents and 8 weeks at 100% pay for non-birthing parents
- Career mobility and internal growth opportunities across the organization
- Professional development budgets for certifications, conferences, and learning available, subject to management approval
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
