Financial Engineer

We are looking for an experienced Python Engineer to join a global Risk Analytics and Financial Engineering environment focused on enabling scalable and efficient credit risk model development. The role sits within a Model Enablement team responsible for supporting risk modelling teams in adopting and effectively using internal analytical toolkits and platforms. The successful candidate will contribute both to the development of Python-based modelling libraries and to collaboration with end users to ensure best practices, usability, and continuous improvement of the tooling ecosystem. This position combines software engineering, quantitative tooling, and stakeholder collaboration in a highly analytical environment supporting large-scale risk modelling initiatives.

• Extensive commercial experience in Python application development
• Strong grasp of object-oriented design and clean coding practices
• Practical experience with test-driven development and testing tools like pytest
• Solid knowledge of coding conventions, identifying code smells, and applying software engineering best practices
• Experience performing code reviews and ensuring consistent code quality
• Good understanding of SOLID principles and widely used design patterns
• Proficient in using Git for version control
• Experience working within Agile software development teams
• Familiarity with CI pipelines and automated testing workflows
• Hands-on experience with the scientific Python stack, including NumPy, SciPy, pandas, polars, and Matplotlib

• Develop and enhance Python-based analytical frameworks used for credit risk modelling
• Design and build scalable, reliable, and maintainable software solutions
• Contribute to large-scale Python libraries, including architecture design, testing, and code quality enhancements
• Work closely with quantitative analysts and risk teams to gather requirements and support adoption of analytical tools
• Promote software engineering best practices, including code reviews and testing standards
• Create automated test suites and support CI/CD-driven development processes
• Collect user feedback and contribute to the ongoing improvement of modelling platforms and analytical tools
• Support rapid prototyping activities related to risk analytics and risk measurement solutions