Quant Engineer
Europe,
United Kingdom,
London
Permanent
Job ID: 2233
Job Description
[c. £175-250k Comp Package | Hybrid Working]
Are you a seasoned Quantitative Engineer with a track record of building high-performance, Python-based risk and pricing systems in financial services? Our client - a leading life and investment management specialist - is seeking an engineer to help drive the next phase of their platform transformation. This is an opportunity to work alongside top talent while shaping a cutting-edge system with Python at its core...
Key Responsibilities
- Architect and enhance Python-based risk and pricing systems, ensuring scalability and robustness
- Develop advanced financial models, optimising performance for real-time pricing and risk calculations
- Work closely with quantitative researchers and traders, implementing new methodologies and improving analytics tools
- Build and maintain high-performance data pipelines for market data processing and risk reporting
- Contribute to DevOps and platform engineering efforts, ensuring seamless integration and deployment
- Provide technical leadership and mentoring to junior engineers, fostering best practices in software development
What You Bring...
- 5-8 years of experience in quantitative engineering, risk, or pricing system development
- Proficiency in Python, with experience in building scalable, production-level financial applications
- Experience working on proprietary risk/pricing platforms at an investment bank or asset management firm
- Strong understanding of financial instruments, particularly Fixed Income and derivatives
- Experience with distributed computing frameworks (e.g., Dask, Ray) for large-scale data processing
- Expertise in data structures, algorithms, and performance optimisation
- Understanding of model risk frameworks and risk management strategies
- (Preferred) Linux/Unix experience, with exposure to cloud computing environments
- (Preferred) Experience with DevOps tooling and CI/CD pipelines
- (Preferred) Contributions to open-source projects or financial libraries
...
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