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Senior Product Analytics Specialist, Property Risk — Marsh McLennan
Develop property risk and loss analytics for Marsh McLennan, covering catastrophe and non-catastrophe scenarios. Turn insurance data and model findings into practical guidance for business and portfolio decisions.
विवरण
- Work with brokers, client leaders, product teams, and analytics partners to define risk and renewal challenges and establish analytical objectives
- Prepare, standardize, and enhance data from exposure, policy, claims, pricing, engineering, and external hazard or vendor models
- Develop, evaluate, and validate Property Risk Quantification models for catastrophe and non-catastrophe applications
- Use pricing, actuarial, and risk-based methods to inform loss modeling, portfolio analysis, and business decisions
- Create prototypes for dashboards, reports, and analytical outputs that make model results actionable
- Partner with product, engineering, and data teams to productionize workflows, strengthen data foundations, and scale analytics capabilities
- Record model assumptions, methods, data lineage, and related documentation in accordance with governance standards
- Help stakeholders interpret model outputs clearly and transparently
- Adapt effectively within a fast-moving incubation environment as priorities, use cases, and scope change
- Structure emerging analytics challenges and drive them toward progress
आवश्यकताएँ
- Bring approximately 5–8 years of relevant experience in analytics, actuarial work, catastrophe modeling, pricing, or insurance risk analysis
- Hold a bachelor’s degree in actuarial science, mathematics, statistics, engineering, economics, data science, or another quantitative field, or offer equivalent practical experience
- Demonstrate a strong grounding in statistical modeling, loss modeling, and model validation, preferably in insurance, pricing, or actuarial settings
- Have experience with catastrophe modeling, property risk analytics, or comparable risk quantification methods
- Have worked with insurance data and related analytical tools
- Experience with RMS, AIR/Verisk, or comparable modeling platforms is advantageous
- Use Python and/or SQL confidently for data preparation, analytics, and modeling
- Have experience building reproducible analytical workflows
- Know BI and visualization tools such as Power BI, Tableau, or equivalent platforms
- A master’s degree in a quantitative discipline or progress toward an actuarial qualification is advantageous
- Bring experience from insurance, reinsurance, broking, or risk advisory, especially property catastrophe and non-catastrophe analytics
- Translate technical findings into useful business recommendations and communicate effectively with varied stakeholders
- Work comfortably in ambiguous, rapidly changing, and lightly structured environments
- Demonstrate a product-oriented approach, shaping methods, refining problem definitions, and adjusting as priorities develop
लाभ
- Hybrid working arrangements with flexibility for remote work
- Opportunities for collaboration, connection, and professional development through office-based work
- A diverse, inclusive, and flexible workplace
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