Data Product Manager

kin; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

Kin is seeking a Data Product Manager to enable data products that drive how pricing, underwriting, actuarial analysis, and claims are handled. You will shape datasets, connect across systems, and partner with data engineering to ship data assets used by pricing and risk teams.

You will own the data layer, ensure the metrics are well-defined, and translate complex multi-source data into actionable recommendations for decision-making across pricing, underwriting, and claims teams.

Qualifications

• 2 to 5 years in product management, data analytics, or an analytical role close to the insurance business.
• Experience translating messy data into usable datasets and insights.
• Strong sense for how data informs pricing, underwriting, actuarial, or claims decisions.

Responsibilities

• Dig past the initial request to reach the real decision the pricing, underwriting, actuarial, or claims team seeks to make.
• Enable data products behind decisions by shaping needed datasets and partnering with data engineering.
• Connect data across systems (e.g., claims stack, vendor models) to understand changes and impacts.
• Build datasets proactively so teams can explore metrics without delays.
• Scope and deliver data products in collaboration with data engineering.
• Own the data layer as the source of truth for core insurance metrics.
• Translate multi-source data into clear narratives and actionable recommendations.
• Collaborate with pricing, actuarial, underwriting, claims, and data engineering to turn insights into decisions.

Skills

Data product management

Data analytics

Insurance domain

Cross-functional collaboration

Job description

Quick Summary

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.

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simpler, more affordable, and better for homeowners, especially in the places where climate risks, rising costs, and outdated systems make it harder.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 .

The opportunity

We’re looking for a data Product Manager to enable the data products behind how Kin prices risk, underwrites policies, runs actuarial analysis, and handles claims. The data that drives those calls lives in many systems, from the claims stack in Snapsheet and Xactimate to vendor loss modeling from RMS and Verisk, alongside our own underwriting and pricing data. This role sits in the middle of that and makes the data usable, so the teams making these decisions can see what is happening and why.

You will enable the data products that drive those decisions rather than owning the calls yourself. That means finding the real question a team is trying to answer and shaping the datasets they need, then partnering with data engineering to build and ship them.

Your 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

Success in this role

In your first 6 to 12 months at Kin, success is less about checking boxes and more about the impact you create. You will 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 will deliver outcomes that make a real difference for both Kinfolk and the homeowners we serve.

By the end of your first year, you should feel confident in your role, trusted as an owner, and proud of the progress you have helped make. The pricing and underwriting decisions in your area are backed by numbers people trust, and the same is becoming true for claims

You have shipped data products that measurably improved an outcome the business cares about, such as loss ratio visibility or pricing accuracy

The teams you support agree on what the key metrics mean and are working from shared, reliable numbers

The data behind those decisions is more reliable and consistent, so calls happen faster and with less second guessing

What you’ll bring

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 fr