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Moody's is seeking an Associate Director of Product Management to lead property underwriting data solutions for European and London Market insurance. This role owns the path to product-market fit, driving evidence-based decisions on where and how the product creates value for insurers.
Key Responsibilities:
- Lead the drive to product-market fit for property underwriting solutions in European and London Market insurance, iterating both product and go-to-market approach with early customers
- Translate customer jobs to be done into technical specifications; work hands-on in data review, defect triage, and feature definition; arbitrate trade-offs between scope, quality, and timeline
- Build a segmented view of how European insurers differ in underwriting practice, data maturity, and systems constraints across countries, between primary and specialty carriers, and including delegated business; translate differences into distinct adoption paths and product design decisions
- Lead the carrier evaluation programme end to end: design evaluations with prospective insurers, structure how findings from early customer usage are captured and themed, and drive prioritized product decisions from evidence
- Iterate go-to-market approach in partnership with sales, marketing, and client success; refine buyer personas, value proposition, pricing, and packaging based on evaluation results and buyer/customer economics
- Hold commercial accountability for the offering, including conversion of evaluations into paid adoption and direct support of business development teams in active pursuits
- Own and advance the business case, financial model, and go-to-market plan through internal investment and stage-gate reviews; report progress and learning to senior leadership
- Coordinate cross-functional dependencies spanning geospatial and property data sourcing, address matching, catastrophe risk analytics, legal and data privacy review; represent the product directly with clients across European markets
The team builds property intelligence and catastrophe risk analytics that insurers use to select, price, and triage individual risks. Products are built on machine learning and computer vision applied to aerial imagery, with active adoption of AI tools in building, evaluating, and supporting them.
Requirements:
- Eight or more years of product management experience, or equivalent combination of product management experience and hands-on experience innovating in property underwriting (e.g., at an insurer or insurance technology provider)
- Demonstrated experience taking a product from concept to market, including new geographic or segment expansion; comfort operating with incomplete information and evolving scope
- Deep knowledge of property and casualty insurance underwriting—how risks are selected, priced, and triaged, and how data and analytics are consumed in those workflows (required)
- Technical depth sufficient to work directly with engineering and data science on data products: fluency with data schemas, model outputs and quality metrics; ability to run structured customer research and convert findings into specifications engineers can build against
- Commercial fluency: ability to build and defend a business case, shape pricing and packaging around customer economics, and hold accountability for adoption and revenue outcomes
- Proven ability to lead and influence engineering, data science, sales, marketing, and client success teams without direct authority; ability to build credibility with senior stakeholders
- Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency; proven ability to implement AI-powered solutions to solve business challenges; growing awareness of AI risk management and commitment to responsible and ethical AI use
- Experience in the London Market (at a Lloyd's syndicate, coverholder, or specialty broker) or with US commercial property exposures written from London strongly valued but not required; familiarity with geospatial data, aerial or satellite imagery, computer vision derived data products, or catastrophe risk modelling also helpful
- Bachelor's degree required; strong candidates come from a wide range of academic backgrounds including engineering, computer science, mathematics, physical sciences, economics, and business
- Advanced degree (master's or MBA) or relevant professional insurance qualification preferred but not required
