DCX Product Analytics Specialist / Senior Analytics Specialist

About the role

We are seeking a talented individual to join our Analytics Solutions team, part of Digital Client Experience at Marsh Risk. The position is based in Zurich or London and focuses on product analytics for property risk quantification, including catastrophe and non‑catastrophe use cases.

Key responsibilities

• Partner with brokers, client executives, product teams and analytics colleagues to identify risk and renewal pain points and translate them into clear analytical problems.
• Prepare, clean and enrich data from multiple sources such as exposure, policies, claims, pricing, engineering and third‑party hazard models.
• Build, assess and validate analytical and loss‑modeling approaches to support property risk quantification.
• Apply pricing, actuarial and risk‑based techniques to generate actionable insights for portfolio assessment and business decision‑making.
• Prototype dashboards, reports and analytical outputs that translate technical model results into decision‑ready guidance.
• Collaborate with product, engineering and data teams to operationalise analytical workflows and improve data foundations.
• Document models, assumptions, methodologies and data lineage in line with governance requirements.
• Operate effectively in a fast‑changing, incubation‑style environment, bringing structure to emerging analytics problems.

Required profile

• 5–8 years of experience in analytics, actuarial work, catastrophe modelling, pricing or insurance risk analysis.
• Bachelor’s degree in a quantitative discipline such as Actuarial Science, Mathematics, Statistics, Engineering, Economics or Data Science.
• Solid understanding of statistical modelling, loss modelling and model validation, preferably in insurance or actuarial contexts.
• Experience with catastrophe modelling, property risk analytics or related risk quantification approaches.
• Familiarity with insurance‑related data and tools; exposure to platforms such as RMS, AIR/Verisk is a plus.

Required skills

• Python
• SQL
• Power BI
• Tableau
• RMS (or similar catastrophe modelling platforms)
• AIR/Verisk (or similar analytics environments)