Data Product Manager

Kin is hiring a Data Product Manager to enable data products supporting insurance pricing, underwriting, actuarial analysis, and claims decisions. The role identifies the decisions teams need to make, shapes the datasets and metrics they rely on, and partners with data engineering to deliver reliable, usable data products.

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

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
• Please only apply if you are able to live and work full-time in one of the states listed above
• Applicants must be able to live and work full-time in Ontario to be considered
• 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