Quantitative Developer - Python

About the role

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 a quantitative development function that works closely with Researchers, Traders and Cloud Engineering teams to build applications, data pipelines and analytics that support research and trading workflows. The role combines software engineering, quantitative development and data engineering, with responsibility for developing production applications, supporting research infrastructure and integrating large scale datasets.

Your future role within QRT

- Design, develop, deploy and maintain cloud native Python applications supporting research and trading workflows, including market data dashboards, risk analytics, profit and loss reporting, weather analytics and performance analysis

- Develop quantitative tools including backtesting frameworks, optimisation tools, pricing libraries and ETL pipelines for integrating and validating alternative datasets

- Build and maintain scalable data pipelines that support model development and production workflows

- Monitor, support, debug and enhance existing research and trading infrastructure

- Work closely with Researchers, Traders and Engineering teams to deliver production quality solutions that meet evolving business requirements

- Provide support for traders and production trading systems as part of a support model that provides continuous coverage across global markets.

Your present skillset

- At least three years of professional Python development experience

- Strong knowledge of Python, including numerical libraries such as NumPy, Pandas, Polars and Xarray

- Strong quantitative mindset with an interest in working closely with trading and research functions

- Experience developing user interfaces or an interest in building data visualisation applications such as Plotly, Dash or Streamlit is beneficial

- Experience with AWS or another cloud platform together with infrastructure as code technologies (e.g. Lambda, S3, DynamoDB, RDS or AWS CDK is advantageous)

- Good knowledge of relational databases such as PostgreSQL together with object storage technologies

- Experience developing ETL pipelines and working with large scale datasets

- Strong understanding of software engineering practices including version control, automated testing, packaging and deployment

- Ability to work independently while collaborating closely with business and technology stakeholders to deliver production solutions