About the Client
We are one of the world’s leading providers of reinsurance, insurance and other forms of insurance-based risk transfer, working to make the world more resilient. We anticipate and manage a wide variety of risks, from natural catastrophes and climate change to cybercrime. Combining experience with creative thinking and cutting-edge expertise, we create new opportunities and solutions for our clients. This is possible thanks to the collaboration of more than 14,000 employees across the world.
About the Role
Build AI that drives real investment decisions. Asset Management’s Tech Transformation is a strategic program to modernise our technology platform and fundamentally reshape how investment decisions are made. We combine transactional and analytics data platforms with cloud and AI technologies to deliver scalable, secure, and high-impact solutions.
Responsibilities
Apply Generative AI to make better investment decisions, better assess new investment opportunities and/or analyze signals in financial markets from unstructured data,
Work across product + engineering + domain experts,
Take ideas from prototype to production, building scalable solutions that are actually used,
Constantly grow our data foundation platform and apply leading edge concepts, such as metadata or graphs,
Support many other exciting projects in a collaborative environment with colleagues from Asset Management's international offices.
Requirements
To be successful in the role, you bring a strong technical foundation and a curiosity to apply it in real-world settings:
Degree in Computer Science, Data Science, Applied Mathematics, Statistics, Physics or related quantitative field. We welcome different levels, including graduates
Knowledge of Typescript and/or Python
Knowledge in machine learning, statistical modelling and related technologies
Nice to Have Skills
Interest or hands-on experience with LLMs / Generative AI (RAG, evaluation, …)
Curiosity about how AI can be applied to financial markets and investment decisions
Interest in agentic AI patterns (tool use, planning, orchestration frameworks)
Background in software engineering
Experience in distributed computing