Fixed Income Risk Engineer (Python) at Qube Research & Technologies (London, United Kingdom)
Qube Research & Technologies· London, United Kingdom·
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 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.
Your future role within QRT
The Risk team build and maintain tools to support risk analysis and reporting for QRT’s trading businesses. This includes close collaboration with Risk Managers, Quantitative Traders, and Quantitative Researchers, across multiple asset classes, to ensure robust and scalable risk infrastructure. This particular opportunity will provide significant contributions for our Fixed Income function.
- Design, build, and maintain production risk analytics tools and data services
- Develop and support data pipelines and reporting systems used by trading and risk teams
- Partner with trading desks, risk, and operations to understand requirements and deliver solutions
- Investigate and resolve data discrepancies, risk inconsistencies, and production issues
- Improve system reliability, performance, and scalability
- Contribute to the evolution of risk and analytics infrastructure
Your present skillset
- Fixed Income Knowledge
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- Solid understanding of Fixed Income products, including bonds, interest rate swaps, bond futures, repos
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- Experience working with trading desks and/or risk teams
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- Understanding of Trade lifecycle; Risk measures (e.g. DV01, sensitivities, stress scenarios); PnL and key risk drivers
- Strong Python development skills
- Experience building and maintaining production systems
- Solid understanding of:
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- Data pipelines and data processing
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- System design and debugging
- Experience with SQL and databases
- Familiarity with APIs and data integrations
- 5+ years of professional software development experience with strong coding ability (Python preferred)
- Experience in a systematic investment manager frim, trading firm, bank, or asset manager is preferred
- Vendor or consultancy experience considered if combined with strong Fixed Income exposure
- Desirable:
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- Experience with distributed systems, cloud platforms, or orchestration tools
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- Experience working in cloud-based environments (AWS preferred) and familiarity with services such as EC2, S3 and Fargate
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- Exposure to containerisation, orchestration, and monitoring tools (e.g. Kubernetes, Grafana) and modern development environments (e.g. CI/CD, Coder)
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.
Why work at Qube Research & Technologies
- 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.