Data Product Manager

Role overview

Enable the data products that power core insurance decisions, from pricing and underwriting to actuarial analysis and claims handling. This role sits between business teams and data engineering, translating real decision questions into reliable datasets that those teams can use to act. It is a hands-on product role focused on making insurance data understandable and trustworthy.

Responsibilities

- Dig past surface requests to uncover the actual decision that pricing, underwriting, actuarial, or claims teams are trying to make. - Shape and deliver the data products that support those decisions, including datasets used in rate reviews and claims views. - Connect data across multiple systems, including claims platforms and vendor loss modeling tools, so changes upstream are understood and handled consistently. - Build supporting datasets proactively, so teams can investigate metrics and problems without waiting for a new data pull. - Partner with data engineering to scope and ship data products, owning the data layer as the single source of truth for core metrics such as loss ratio and pricing accuracy. - Define what each metric means before it ships, since the outputs influence rate and risk selection decisions. - Improve data quality and instrumentation, and translate multi-source data into a clear story with a recommendation someone can act on.

Requirements

- Experience working closely with data engineering and analytics teams to deliver datasets used for business decisions. - Comfort navigating a mix of internal systems and third-party vendor data, including claims and loss-modeling sources. - Ability to define metrics carefully and ensure they are documented and trusted before being used in financial decisions. - Strong communication skills to translate messy, multi-source data into clear narratives and actionable recommendations. - Track record of partnering across functions such as pricing, actuarial, underwriting, and claims.

Nice to have

- Prior experience in insurance, financial services, or another regulated industry where data drives pricing or risk decisions. - Familiarity with vendor loss modeling platforms or claims management systems.