Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and develop innovative Python applications for trading and data analysis.
- Company: Join a global leader in quantitative investment with a culture of innovation.
- Benefits: Enjoy a healthy work-life balance and diverse workplace initiatives.
- Why this job: Make an impact in the commodities market using cutting-edge technology.
- Qualifications: Strong Python skills and experience in financial environments are essential.
- Other info: Collaborate with experts and grow your career in a dynamic team.
The predicted salary is between 36000 - 60000 £ per year.
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.
Your future role within QRT:
- 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.
Requirements:
- 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.
Quantitative Developer - Commodities (Python) employer: Qube Research & Technologies
Contact Detail:
Qube Research & Technologies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Developer - Commodities (Python)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at QRT. LinkedIn is your best mate here—connect with current employees and ask for insights about their work culture and projects.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio of projects or GitHub repositories, make sure to highlight them. Demonstrating your Python prowess and any quantitative tools you've built can really set you apart.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and quantitative skills. Practice coding challenges and be ready to discuss your thought process. We want to see how you tackle problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at QRT.
We think you need these skills to ace Quantitative Developer - Commodities (Python)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and any relevant quantitative tools. We want to see how your skills align with the role, so don’t be shy about showcasing your front-office financial experience!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re excited about the Quantitative Developer role and how your background in data analysis and cloud-native applications makes you a perfect fit for our team.
Showcase Your Projects: If you've worked on any cool projects involving ETL pipelines or data visualisation, make sure to mention them! We love seeing practical examples of your work, especially if they relate to commodities or financial markets.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen to join our innovative team!
How to prepare for a job interview at Qube Research & Technologies
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially the numerical libraries like numpy and pandas. Be ready to discuss how you've used these in a production environment, as well as any specific projects where you developed full-stack applications.
✨Showcase Your Quantitative Mindset
Prepare to demonstrate your quantitative skills and how they apply to trading and risk management. Think of examples where you've built tools or models that supported trading decisions, and be ready to explain your thought process behind them.
✨Familiarise Yourself with Cloud Technologies
Since the role involves cloud-native applications, make sure you understand AWS services like Lambda and S3. Be prepared to discuss any experience you have with infrastructure-as-code and how it can enhance development processes.
✨Engage with Front-Office Users
This position requires collaboration with Researchers and Traders, so practice articulating your ideas clearly. Think about how you can effectively communicate technical concepts to non-technical stakeholders, and be ready to share experiences where you've done this successfully.
