M
Marsh
Analytics Engineer
DCX Product Analytics Specialist / Senior Analytics Specialist
On-siteSeniorAnalytics Engineerposted 4d ago
Role summaryAI-generated
Marsh is looking for a DCX Product Analytics Specialist to partner with brokers and product teams in Zurich or London, turning risk and renewal pain points into actionable analytical solutions. The role involves cleaning and enriching multi-source data, building and validating loss and catastrophe models to support property risk quantification.
Skills required
About this role
Company:
MarshDescription:
We are seeking a talented individual to join our Analytics Solutions team, part of Digital Client Experience at Marsh Risk. This role will be based in Zurich or London.
DCX Product Analytics Specialist / Senior Analytics Specialist
We will count on you to:
- Partner with brokers, client executives, product teams, and analytics colleagues to identify risk and renewal pain points and translate them into clear analytical problems and success criteria.
- Prepare, clean, and enrich data from multiple sources including exposure, policies, claims, pricing, engineering, and third-party hazard or vendor model data.
- Build, assess, and validate analytical models and loss modeling approaches to support Property Risk Quantification, including catastrophe and non-catastrophe use cases, with potential application across other lines of business.
- Apply pricing, actuarial, and risk-based techniques to generate actionable insights for loss modeling, portfolio assessment, and business decision-making.
- Prototype dashboards, reports, and analytical outputs that translate technical model results into clear, decision-ready guidance for business stakeholders.
- Collaborate closely with product, engineering, and data teams to operationalize analytical workflows, improve data foundations, and support scalable analytics solutions.
- Document models, assumptions, methodologies, and data lineage in line with governance requirements and support transparent interpretation of model outputs.
- Operate effectively in a fast-changing, incubation-style environment where priorities, use cases, and project scope may evolve, helping bring structure and momentum to emerging analytics problems.
What you need to have:
- Typically 5–8 years of relevant experience in analytics, actuarial work, catastrophe modeling, pricing, or insurance risk analysis.
- Bachelor’s degree in a quantitative discipline such as Actuarial Science, Mathematics, Statistics, Engineering, Economics, Data Science, or equivalent practical experience.
- Solid understanding of statistical modeling, loss modeling, and model validation, ideally in insurance, pricing, or actuarial contexts.
- Experience with catastrophe modeling, Property risk analytics, or related risk quantification approaches, including interpretation and use of model outputs.
- Experience working with insurance-related data and tools, with familiarity with platforms such as RMS, AIR/Verisk, or similar analytics and modeling environments considered a plus.
- Proficiency in Python and/or SQL for analytics, modeling, and data preparation, with experience in reproducible analytical workflows.
- Familiarity with BI and visualization tools such as Power BI, Tableau, or similar tools to create prototype dashboards and business-ready analytical outputs.
What makes you stand out:
- Master’s degree in a quantitative field or progress toward an actuarial qualification.
- Experience working in insurance, reinsurance, broking, or risk advisory, particularly in Property cat and non-cat analytics.
- Demonstrated ability to translate technical results into actionable business insights and communicate effectively with diverse stakeholders.
- Comfort working in ambiguous, fast-changing, and not fully structured environments, with the ability to create clarity and move work forward.
- Product mindset with the ability to shape approaches, refine problem statements, and adapt as priorities evolve in an incubation-style setting.
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