Quantitative Developer

Quick Facts

Quantitative Developer to build and enhance a data-driven platform for quantitative research, analytics, and automated decision-making.

Description

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.

Responsibilities

• Develop and maintain Python applications and frameworks for quantitative research, strategy development, simulation, and production workflows
• Build scalable data pipelines for processing large volumes of historical and real-time financial data
• Design and optimize SQL databases and data models to support analytics, reporting, and research
• Work with quantitative researchers and investment professionals to turn analytical concepts into reliable, production-ready solutions
• Create tools for model validation, performance analysis, experiment tracking, and strategy evaluation
• Enhance system performance, automation, monitoring, and operational resilience across research and production environments
• Support deployment, testing, troubleshooting, and ongoing maintenance of Linux-based applications
• Contribute to architectural decisions and the long-term evolution of the quantitative technology platform
• Mentor team members and promote 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 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

Benefits

Not specified in the provided text.