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 join a front-office quantitative development team that works closely with Researchers and Traders in QRT’s global Commodities business. The team is responsible for building tools, models, and infrastructure that support trading decisions, data analysis, and risk management.

• Design, develop, and deploy full-stack cloud-native Python applications in collaboration with Research, Trading, and Cloud teams (e.g. market data dashboards, PnL and risk tools, trade flow explorers)
• Build quantitative tools to support research and trading, including backtesters, pricers, optimisers, and ETL pipelines for complex datasets (e.g. weather, balance sheets)
• Monitor, debug, and enhance existing Commodities trading and research infrastructure
• Support alternative data engineering initiatives and model training at scale

• Significant experience with Python in a production environment
• Strong knowledge of Python numerical libraries (e.g. numpy, pandas, xarray)
• Front-office financial experience and a strong quantitative mindset
• Experience developing ETL pipelines and working with structured/unstructured data
• Familiarity with PostgreSQL or other relational databases
• Experience with infrastructure-as-code and cloud platforms (AWS preferred)
• Working knowledge of software development best practices (Git, testing, packaging)
• Comfortable engaging directly with front-office users and collaborating across teams
• Willingness to develop UI components or work with data visualisation libraries

• Experience with data visualisation frameworks (e.g. Plotly, Dash, Streamlit, htmx) is desirable
• Advanced AWS experience (e.g. Lambda, S3, DynamoDB, AWS CDK) is beneficial
• In-depth database optimisation and knowledge of relational vs non-relational models is advantageous
• Exposure to parallel or distributed computing is a plus
• Modelling experience or previous Commodities domain knowledge (especially Metals or Agriculture) is desirable

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.