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
Join a high-impact team building a distributed analytics platform on Private cloud and Azure cloud.
You’ll contribute to the evolution of our Python-based compute grid and collaborate with quantitative analysts to deliver scalable, high-performance analytics.
Responsibilities
Extend and optimize our distributed analytics platform for risk and valuation workloads
Build and maintain asynchronous processing pipelines
Collaborate with internal clients and cross-functional teams to deliver robust solutions
Contribute to cloud-native deployments and performance tuning across Private cloud and Azure
Support production workflows and provide instructions for adjustments
Requirements
Advanced Python programming skills, including asyncio and multiprocessing
Strong analytical and problem-solving skills
Experience with RESTful APIs, RPC protocols and batch processing
Deep understanding of database systems: querying languages, transactions, security, relational vs NoSQL
Experience with fast in-memory caching strategies – Redis, Memcached
Long-term experience with Unix/Linux environments and shell scripting
Nice to Have Skills
NoSQL databases - MongoDB, Cosmos DB
Cloud platforms - Azure, PaaS
Containerization (Docker) and orchestration
Authentication mechanisms – Kerberos, OAuth2, SSO
Financial instruments: e.g. options, bonds, swaps
Familiarity with risk analytics and valuation models
GPU-based computation
Understanding AI tools