Senior Quantitative Developer – Commodities

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 QRT’s 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.

The team:

The Commodities Front Office Quantitative Development team works closely with researchers and traders across QRT’s global Commodities business. We are looking to strengthen our technology capabilities supporting the Agriculture business. The team builds research and trading platforms covering market, alternative, weather and remote-sensing data, as well as quantitative modelling, risk management, trade flows and performance analysis.

Our stack combines Python for quantitative computing, data engineering and backend services; React and TypeScript for analytical applications; SQL and cloud-native storage; and AWS infrastructure managed through Infrastructure-as-Code.

Your future role within QRT:

• Design, develop, deploy and support cloud-native applications for commodities research and trading.
• Build full-stack analytical tools using Python backend services and React/TypeScript front ends.
• Develop research infrastructure, including data pipelines, backtesting frameworks, optimisers, APIs and scalable modelling workflows.
• Integrate and process market, fundamental, weather, geospatial, remote-sensing and alternative datasets.
• Help researchers transition exploratory workflows into reliable production systems.
• Maintain high standards for data quality, reproducibility, monitoring and point-in-time correctness.
• Collaborate with researchers, traders, data engineers and infrastructure teams across multiple locations.
• Evaluate modern technologies and AI-assisted development tools where they can improve research and engineering productivity.

Your present skill set:

• At least 5 years of professional software development experience, with advanced Python expertise and strong software engineering and system design fundamentals.
• Strong knowledge of numerical and analytical Python libraries such as NumPy, pandas, Polars and xarray.
• Experience building production-grade Python services, APIs and data pipelines.
• Strong experience with React, TypeScript, SQL and relational databases.
• Experience working with weather, geospatial, remote-sensing or other large scientific datasets.
• Familiarity with relevant data technologies and formats, such as GeoPandas, rasterio, STAC, Zarr, NetCDF, GRIB, Parquet and Arrow.
• Experience scaling data-intensive or computational workloads using frameworks such as Dask, Ray or Spark.
• Hands-on cloud experience, ideally with AWS, including Infrastructure-as-Code, containers and CI/CD.
• Strong quantitative mindset and the ability to work directly with researchers and traders, taking projects from requirements through to production.
• A rigorous approach to engineering, testing and code review, including when using AI-assisted development tools.

Nice to have:

• Front-office trading or quantitative-finance experience.
• Commodities experience, particularly within Agriculture.
• Experience with Airflow or a similar orchestration platform.
• Strong AWS architecture experience.
• Familiarity with machine-learning infrastructure and model-training pipelines.