Mid-Level, Senior
Join Aon’s View of Risk Advisory team to build the next generation of data, analytics and AI tools used by risk professionals worldwide. This is a full-time hybrid role with the flexibility to work both virtually and from our Prague office.
You’ll design and deliver scalable data and AI solutions that connect complex catastrophe model outputs, scientific research and technical documentation with the people who need them. Working across structured data, unstructured content and AI-assisted workflows, you’ll help our global teams make better, faster decisions. You’ll collaborate with Data Engineers, Scientists, Analysts and Catastrophe Modellers, using modern cloud analytics platforms to build robust data pipelines, analytical data products and retrieval systems for model and document intelligence. You’ll also integrate LLM and AI capabilities into real-world analytical workflows.
Being part of Aon means working in a driven, encouraging, and friendly environment that values integrity, authenticity, and a can‑do approach, within a global leader in the attractive reinsurance industry and its regional headquarters in Prague. We offer flexible working, modern offices in the city centre, home office options, and an attractive compensation package including pension scheme contributions, in‑office massages, language courses, ergonomic tables, sick days, and more.
Strong experience with Databricks, Apache Spark and Delta Lake
Advanced SQL for analytical querying, optimisation and data modelling
Strong Python development skills (testing, version control, engineering best practices)
Proven track record building and operating ETL/ELT pipelines from APIs, databases and third-party data
Experience creating and managing analytical data products
Exposure to document ingestion, indexing, search/retrieval systems or knowledge management
Familiarity with AI / ML / LLM-enabled workflows and interest in applying them to real-world risk problems
We welcome candidates from a range of analytical and technical backgrounds, including insurance or reinsurance analytics, catastrophe modelling, climate or earth sciences, geospatial analytics, financial analytics and other quantitative disciplines. Catastrophe modelling experience is an advantage but not essential – curiosity, strong data engineering skills and the ability to learn complex domains matter most.
#LI-BK2 2026-104295
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