Drive innovative market risk technology by combining Python development, quantitative research, financial modelling, scalable data workflows, and financial markets expertise to strengthen risk measurement and decision-making.

What You'll Do:

Join a highly collaborative quantitative technology environment where software engineering and quantitative research come together to solve complex market risk challenges across diverse trading businesses, products, and asset classes.

You will:

Develop robust Python-based solutions for market risk monitoring, measurement, management, and hedging.
Build and enhance financial instrument models and quantitative risk methodologies.
Work with large-scale daily and intraday datasets to uncover insights and improve decision-making.
Design scalable data, computation, visualisation, and workflow solutions.
Conduct empirical research and translate quantitative methods into practical software applications.
Collaborate closely with researchers, developers, traders, and risk professionals.
Continuously improve engineering practices through agile development and CI/CD.
Learn new financial concepts, technologies, and methodologies rapidly to address evolving business requirements.

Your responsibilities will include:

Developing production-quality quantitative software using Python and tools such as Pandas, Polars, NumPy, and SciPy.
Supporting market risk analytics across multiple financial instruments, markets, and asset classes.
Transforming complex datasets into reliable, actionable risk information.
Building maintainable systems capable of operating efficiently at scale.
Applying quantitative and statistical techniques to real-world financial problems.
Contributing to instrument modelling, risk measurement, empirical analysis, and hedging capabilities.
Working within distributed Linux environments and collaborating on modern software development practices.
Challenging existing approaches constructively and identifying opportunities for continuous improvement.
Taking ownership of projects from initial concept through development, deployment, and ongoing enhancement.

Why Join Us:

This is an opportunity to work at the intersection ofquantitative finance, software engineering, data science, and market risk . You will tackle intellectually demanding problems while developing technology that directly influences financial decision-making.

The role offers significant exposure to financial markets, sophisticated quantitative methodologies, large-scale data, and high-performance technology. It is particularly suited to someone who enjoys learning, solving unfamiliar problems, and turning complex ideas into practical, scalable solutions.

About You:

You bring5+ years of relevant technical experience , strong Python programming capabilities, and a solid understanding of financial markets.

Ideally, you have:

A CFA Charter or equivalent foundational knowledge of financial markets.
A Bachelor's or Master's degree in Financial Engineering, Finance, Statistics, or a related discipline.
Direct experience working with at least one financial asset class.
Practical experience handling data at scale, including daily or intraday datasets.
Experience with CI/CD frameworks and agile software development.
Strong written and verbal communication skills.
A self-directed approach with genuine ownership and accountability.
Curiosity and enthusiasm for learning substantial new concepts independently.
Familiarity with C++ and columnar databases or data technologies is advantageous.
Experience with financial instrument modelling or empirical research is highly desirable.

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