Quantitative Engineer Position
We're seeking an experienced Quantitative Engineer to join our team.
The successful candidate will be part of a high-performing team building critical investment and risk modelling tools across asset classes and liabilities.
This role requires a strong background in software/platform development with experience in C#/.NET, as well as a practical understanding of banking or asset management, particularly risk and pricing systems.
Develop hands-on with C#/.NET in a collaborative environment to build critical investment and risk modelling tools.
Collaborate with quantitative analysts, actuaries, and developers to design and enhance risk and investment models.
Translate complex Excel-based models into robust, maintainable production code using C#.
Build and maintain core pricing and valuation libraries for interest rates, FX, credit, derivatives, annuities, and reinsurance.
Onboard new investment strategies, annuity products and instruments into modelling and risk platforms.
Develop assistive tools to support actuarial modelling, ALM hedge strategies, and internal trade support.
Investigate the application of AI/ML for modelling efficiency, anomaly detection, and enhanced user tooling (e.g., Excel-integrated chatbots).
Requirements
A minimum of 5-7 years of experience in software/platform development with strong delivery ownership.
Strong knowledge of financial instruments and quantitative models.
Understanding of market risk, fixed income, and/or actuarial modelling highly regarded.
A solid understanding of SQL Server/PostgreSQL and performant data handling.
About This Role
This is an exciting opportunity for an ambitious professional to thrive in a hybrid environment of quantitative rigour and software engineering excellence.
Technical Skills Required
Strong C#/.NET (Framework 4.8 and Core) with experience in LINQ, Entity Framework, and RESTful APIs.
Familiarity with C++ for performance-critical or legacy pricing components.
Exposure to Python for prototyping, data analysis, or AI experimentation.
Experience using Git, NUnit/xUnit, and CI/CD pipelines (e.g., Azure DevOps).
Domain Knowledge
Strong knowledge of financial instruments and quantitative models.
Understanding of market risk, fixed income, and/or actuarial modelling highly regarded.
Education
Bachelor's degree in Computer Science, Applied Mathematics, Engineering, or related field.
Postgraduate qualification or actuarial training advantageous.