Quantitative Developer - Commodities (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 work within a quantitative development function supporting research and trading activities across Commodities, including Agriculture, Metals and Energy. The role focuses on developing Python applications, quantitative tools and data infrastructure that support trading decisions, research and risk management. You will collaborate closely with Quantitative Researchers, Traders, Data Engineers and infrastructure specialists to deliver solutions across alternative data, pricing, backtesting and statistical modelling.

Your future role within QRT

Design, develop and deploy quantitative tools supporting trading and research, including pricing, backtesting, risk analysis and PnL reporting

Build Python applications and data pipelines to explore, integrate and analyse alternative datasets, including weather and cargo data

Collaborate with Quantitative Researchers and Traders to translate trading ideas and business requirements into production applications and quantitative models

Architect, develop and maintain cloud applications in collaboration with infrastructure engineers, using AWS and related technologies

Develop and apply statistical and machine learning models to support research and trading across Agriculture, Metals and Energy

Implement quantitative optimisation methods and automate research and trading workflows

Monitor, troubleshoot and enhance existing trading and research infrastructure to ensure reliability and performance

Your present skillset

Minimum 2 years of professional software development experience, with strong Python programming skills or proficiency in another object oriented language

Strong understanding of software design principles and experience developing maintainable applications

Proficiency with Python numerical and data analysis libraries such as NumPy, Pandas, Polars and Matplotlib

Solid SQL skills and experience working with relational databases

Experience developing data processing pipelines, ideally using orchestration frameworks such as Airflow

Familiarity with AWS or similar cloud platforms and infrastructure as code practices

Good understanding of software development practices, including Git, unit testing, packaging and scripting

Experience using AI development tools to support coding, debugging and software delivery

Strong quantitative and analytical skills, with an interest in financial markets and trading

Ability to work autonomously, manage priorities and collaborate effectively with Researchers, Traders and Engineers

Previous experience developing quantitative tools or models within Commodities trading is beneficial

Experience building dashboards and data visualisation applications using Plotly, Streamlit, Dash or htmx is advantageous

Advanced AWS experience, including services such as DynamoDB, RDS, S3, Lambda and AWS CDK, is beneficial

Familiarity with Snowflake or similar data platforms is advantageous

Experience with parallel or distributed computing frameworks such as Slurm and Ray is beneficial

Experience developing statistical or machine learning models is advantageous