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Kin Insurance is seeking a Data Product Manager to enable the data products that power core insurance decisions—pricing, underwriting, actuarial analysis, and claims handling. The role sits at the intersection of multiple data systems (Snapsheet, Xactimate, RMS, Verisk) and internal underwriting/pricing data, making that information usable and actionable for decision-makers.
You will not own the insurance decisions themselves, but rather enable the teams making them by uncovering the real business question behind each request and partnering with data engineering to build the datasets those teams rely on. This is a product role focused on data infrastructure and analytics enablement.
Key responsibilities include:
- Dig past surface-level requests to understand the actual decision a team is trying to make
- Enable data products that drive pricing, underwriting, actuarial, and claims decisions
- Connect data across multiple systems so changes are understood and handled consistently
- Build supporting datasets proactively so teams can self-serve analysis without waiting for new pulls
- Scope and deliver data products in partnership with data engineering
- Own the data layer as the single source of truth for core insurance metrics (loss ratio, pricing accuracy, etc.)
- Define metrics precisely before they ship, since they drive real money decisions
- Improve data quality and instrumentation to build trust in the numbers
- Translate multi-source data into clear stories and actionable recommendations
- Partner across pricing, actuarial, underwriting, claims, and data engineering teams
Success in the first 12 months means shipping data products that measurably improve business outcomes (e.g., loss ratio visibility, pricing accuracy), establishing shared definitions and reliable metrics across teams, and building a data layer that enables faster, more confident decision-making with less second-guessing.
Kin is a remote-first, profitable insurtech company founded in 2016, serving homeowners in 14 states with a focus on climate-resilient, affordable coverage. The company has been recognized by Built In Chicago, Forbes (Fintech 50, Best Startup Employers), and Great Places to 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 make decisions, ideally from time spent as an analyst making recommendations (not only shipping features)
- Advanced SQL; able to pull and join data across multiple sources independently
- Comfort with modern data stacks (e.g., Databricks, Looker)
- Instinct to dig for the real question instead of taking the first request at face value
- Precision about definitions—metrics driving pricing or claims decisions must mean one thing
- Ability to use AI to raise throughput and prototype ideas quickly
- Experience partnering with engineering to scope and ship
- Some familiarity with insurance business, or clear appetite to learn it fast
- Clear, concise communication with both technical and business audiences
BONUS:
- Background in InsurTech or FinTech, especially homeowners insurance
- Comfort with concepts like loss ratio, premium, underwriting, catastrophe risk
- Familiarity with insurance systems (Snapsheet, Xactimate, RMS, Verisk catastrophe modeling)
