Quantitative Developer - Python

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

You will join our Research Platform team as an integral member. Our team collaborates closely to solve challenging problems that directly impact quantitative research at scale. In this role, you will contribute to the development and evolution of our next-generation research platform, which enables researchers to design, test, and deploy highly complex quantitative strategies. This team is central to our business success, supporting distributed computation, large-scale backtesting, and rapid experimentation.

Key aspects of the project include distributed systems development, scalable data processing, and building a platform that is fast, reliable, and user-friendly. Our primary language is Python and we live in an ecosystem that increasingly utilizes Rust. Experience in financial data or quantitative development is advantageous but not essential. We welcome talented developers without a background in financial services and are committed to providing training and guidance.

Your future role within QRT

• Developing user-friendly APIs for Research use
• Designing and developing a scalable, robust platform for quantitative research
• Writing automated tests and maintaining high code quality
• Integrating Research Workflows with Strategy Deployment and Production
• Developing reusable libraries and APIs
• Collaborating with researchers and engineering teams to propose and implement new framework features

Your present skillset

• Experience and knowledge in distributed systems and large-scale data processing
• Proficiency in Python and research-oriented APIs
• Familiarity with Rust is helpful, but not required
• Understanding of parallel computation
• Knowledge of testing within continuous delivery and integration pipelines
• Familiarity with Ray, Spark or other MapReduce technologies
• Excellent communication skills, with the ability to collaborate effectively in a small, close-knit team
• Familiarity with cloud technologies (AWS preferred)
• Fluency in English