Quantitative Developer

We are looking for a Quantitative Developer to help build and enhance a data-driven platform used for quantitative research, analytics, and automated decision-making. The role combines software engineering, market data management, and quantitative problem solving, with a strong focus on Python development, SQL-based data processing, and Linux-based environments.

Key responsibilities include:

Developing and maintaining Python applications and frameworks that support quantitative research, strategy development, simulation, and production workflows.

Building scalable data pipelines for processing large volumes of historical and real-time financial data.

Designing and optimizing SQL databases and data models to support analytics, reporting, and research activities.

Working closely with quantitative researchers and investment professionals to convert analytical concepts into reliable, production-ready solutions.

Creating tools for model validation, performance analysis, experiment tracking, and strategy evaluation.

Enhancing system performance, automation, monitoring, and operational resilience across research and production environments.

Supporting deployment, testing, troubleshooting, and ongoing maintenance of applications running on Linux infrastructure.

Contributing to architectural decisions and the long-term evolution of the quantitative technology platform.

Mentoring team members and promoting engineering best practices, code quality, and continuous improvement.

Requirements

Degree in Computer Science, Mathematics, Physics, Engineering, Finance, or another quantitative discipline.

Commercial experience developing software solutions in Python within data-intensive or quantitative environments.

Strong SQL skills, including database design, query optimization, and processing large datasets.

Hands-on experience working in Linux-based environments for development, deployment, and operational support.

Experience building data processing platforms, analytics systems, or research tooling used for quantitative decision-making.

Understanding of software engineering best practices including testing, version control, CI/CD, monitoring, and production support.

Ability to analyze complex datasets, identify patterns, and solve quantitative or statistical problems.

Familiarity with financial markets, market data, trading systems, risk analytics, or quantitative modelling is highly desirable.

Exposure to performance optimization, distributed systems, or high-throughput data processing environments is a plus.

Experience with C++ or other compiled languages is beneficial but not essential.

Strong communication skills and experience collaborating with technical and non-technical stakeholders.

High level of professionalism, ownership, and attention to detail.