--- title: 'Quantitative Developer - Commodities (Python) at Qube Research & Technologies' canonical: 'https://feeny.ai/job/quantitative-developer-commodities-python-qube-research-technologies-london-k2zwx1gvzgfw' type: 'job' last_seen: '2026-10-31' --- # Quantitative Developer - Commodities (Python) at Qube Research & Technologies - **Company:** Qube Research & Technologies - **Location:** London, United Kingdom - **Posted:** 2026-10-30 - **Last confirmed live:** 2026-10-31 - **Apply:** https://job-boards.greenhouse.io/quberesearchandtechnologies/jobs/8924911002 ## Job description 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 - Previous experience mentoring junior developers or interns is beneficial 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. ## About Qube Research & Technologies ## Company Overview - **One-liner**: Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager that deploys data, research, and technology to execute multi-strategy trading across all asset classes. - **Entity Type**: Private (Privately Held) - **Headquarters**: London, United Kingdom - **Founded**: 2018 (spun off from a systematic trading team at Credit Suisse, with roots tracing to 2016) - **Founders**: Not publicly disclosed (spun out of Credit Suisse's systematic trading team) ## Core Business - **Primary industry**: Financial Services / Quantitative Hedge Fund / Systematic Investment Management - **Target customers**: Institutional investors (pension funds, sovereign wealth funds, endowments, and other large allocators) - **Mission/purpose**: To combine data, research, technology, and trading expertise to solve complex challenges and deliver high-quality returns for investors. ## Products & Services - **Multi-Strategy Investment Management**: QRT deploys a diverse range of investment strategies across geographies, asset classes (equities, fixed income, FX, commodities, crypto), and time frames (high-frequency to long-term). They operate as a systematic, data-driven hedge fund. - **Quantitative Research & Technology Platform**: The firm's core offering is its proprietary technology and research platform, which enables quantitative researchers, data scientists, and software engineers to develop and execute trading models at scale. ## Market Standing - **Valuation/Market Cap**: Not disclosed (privately held) - **Key Metric**: Total Funding: Not applicable (privately held, profitable firm). **Assets Under Management (AUM)**: Added $4bn in AUM between the start of 2024 and May 2024, returning 22% from January to April 2024 according to reports. - **Notable Investors/Partners**: Institutional investors (pension funds, sovereign wealth funds, endowments). Spun off from Credit Suisse's systematic trading team. - **Growth Signals**: Headcount grew **+56.4% YoY** to 1,787 employees. Expanded to 16 offices across 24 countries (including new offices in Dubai, Chicago, and New York). Over 100 active job openings. AUM grew significantly in 2024. ## Competitive Advantages - **Data & Technology Moat**: Combines proprietary research, massive datasets, and advanced technology (including machine learning, low-latency C++/FPGA systems, and cloud infrastructure) to generate alpha across all asset classes and timeframes. - **Multi-Strategy, Multi-Asset Diversification**: Operates across geographies, asset classes, and time horizons, reducing single-strategy risk and allowing capital to flow to the best opportunities. - **Talent Density & Culture**: Rapidly hires top talent from competitors (Goldman Sachs, Citadel, Millennium, Credit Suisse) and top universities. A young, high-performance culture with 74% of staff aged 40 or under. - **Compensation Model**: Over 40% of staff are part of a deferred compensation plan with exposure to fund performance, aligning employee incentives directly with investor returns. ## Strategic Focus - **Aggressive Global Expansion**: Rapidly scaling headcount (+56% YoY) and opening new offices in key financial hubs (Dubai, Chicago, New York, Singapore, Hong Kong). - **Technology & Infrastructure Investment**: Heavy investment in low-latency trading systems, FPGA engineering, cloud infrastructure, and data platforms (Snowflake, Python, C++, C#). - **Talent Acquisition**: Prioritizing hiring top quantitative researchers, software engineers, data scientists, and traders from competitors and top universities. Over 100 open roles globally. - **Crypto & New Asset Classes**: Actively building a crypto trading team and expanding into new asset classes and geographies. ## Why Work Here - **Compensation & Career Growth**: Highly competitive pay. Interns can earn around $12k per month. Over 40% of staff are in a deferred compensation plan with exposure to fund performance. Glassdoor rating of 4.1/5.0, with compensation (4.0) and career opportunities (4.1) as top highlights. - **Culture & Demographics**: Young, high-performance culture (74% of staff aged 40 or under, 38% aged 30 or under). 90% of staff reported good team morale in an internal survey. Described as a "fertile ground for experimental research." - **Work Environment**: Hybrid/office-based depending on role and location. Offices in London (HQ), Paris, Hong Kong, Singapore, New York, Chicago, Dubai, Mumbai, Geneva, and more. New London office in Victoria. - **Notable Perks**: Deferred compensation plan with fund performance exposure. Interns can earn around $12k per month. Strong focus on work-life balance initiatives. - **Engineering Culture**: Heavy emphasis on technology (Python, C++, C#, Snowflake, FPGA, low-latency systems, MLflow, Kubernetes). 22% of staff are in Research roles, 6% in Technical roles. Strong support for coding initiatives and academic projects in maths and science. ## Sources 1. [qube-rt.com](https://www.qube-rt.com/) 2. [LinkedIn](https://www.linkedin.com/company/qube-rt) 3. [efinancialcareers-canada.com](https://www.efinancialcareers-canada.com/news/qube-research-and-technologies-hiring-and-culture) 4. [Greenhouse Job Board](http://job-boards.greenhouse.io/quberesearchandtechnologies?page=2) 5. 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