Interested in being part of a growing, specialised team developing an award-winning SaaS analytics platform used to assess over £200bn of non-life insurance business?
This is a mid to senior level software engineering role focused heavily on production-grade Python development.
This is not a web-facing CRUD or API-endpoint development role. The core focus of this position is building high-performance computational pipelines, optimising memory for large datasets, and engineering mathematical/analytical engines, you will need relevant experience in this space to be considered.
This is a hybrid role based in London (2 days per week in office).
The role:
- Technical Challenge: Take ownership of performance bottlenecks involving 4GB+ datasets.
- Architectural Input: Taking new features from conception to deployment
- Production-Grade Python: Apply software engineering best practices including OOP, unit testing, and CI/CD.
- Mathematical/ Financial Logic: Translating complex analytical, mathematical, or financial logic into reusable, production-grade software tools.
What We Are Looking For:
- Production-Grade Python: Strong experience writing clean, modular, and maintainable Python code (classes/functions, separation of concerns) within a professional software engineering environment.
- Large Dataset Management: Proven track record of preventing memory overheads and optimizing execution speeds when manipulating massive (GB-scale) datasets. Focusing on performance bottlenecks via vectorisation, parallelism, chunking, or memory optimization.
- Analytical Pipelines: Experience building end-to-end analytical pipelines (data ingestion → computational transformation → modelling → output) rather than one-off analyses.
- Cloud Environments: Hands-on exposure to deploying and managing applications within a cloud environment (AWS, GCP, or Azure) and an understanding of how components fit together (API → compute → storage).
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