Senior Python Developer

Senior Python Engineer role in a global Risk Analytics and Financial Engineering environment focused on credit risk model development. The position is within a Model Enablement team supporting risk modelling teams with internal analytical toolkits and platforms.

• Strong commercial experience in Python software development.
• Solid understanding of object-oriented programming and clean code principles.
• Hands-on experience with test-driven development and testing frameworks such as pytest.
• Strong understanding of coding standards, code smells, and software engineering best practices.
• Experience conducting code reviews and maintaining high code quality standards.
• Practical knowledge of SOLID principles and common design patterns.
• Good knowledge of Git version control.
• Experience working in Agile development environments.
• Familiarity with continuous integration and automated testing practices.

Nice to have:

• MSc or PhD in Computer Science, Mathematics, Physics, Operational Research, Informatics, or a related technical field.
• Exposure to credit risk analytics or financial risk modelling environments.
• Experience with scientific Python ecosystem tools such as NumPy, SciPy, pandas, polars, and Matplotlib.
• Experience working with PySpark or other Big Data technologies.
• Background in developing reusable Python libraries or contributing to open-source projects.

• Develop and maintain Python-based analytical toolkits used in credit risk modelling.
• Design and implement robust, scalable, and maintainable software solutions.
• Contribute to large Python libraries, including architecture, testing, and code quality improvements.
• Collaborate closely with quantitative analysts and risk modelling teams to understand requirements and support toolkit adoption.
• Drive best practices in software engineering, code review, and testing.
• Develop automated testing suites and contribute to CI/CD-oriented development workflows.
• Gather user feedback and help shape future improvements of modelling platforms and tools.
• Support rapid prototyping initiatives related to risk analytics and risk measurement.