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- Tasks: Build core research infrastructure for alpha generation and solve complex quantitative problems.
- Company: Globally recognised tech-driven trading firm at the forefront of quantitative research.
- Benefits: Competitive salary, bonus, high autonomy, and clear progression opportunities.
- Why this job: Make a real impact on trading strategies while working with cutting-edge tools and large datasets.
- Qualifications: 5+ years Python experience in quantitative finance and strong problem-solving skills.
- Other info: Collaborate directly with quants and enjoy a performance-driven culture.
The predicted salary is between 130000 - 220000 £ per year.
Location: London (Hybrid)
Salary: £130,000 - £220,000 + Bonus
We are working with a globally recognised, technology-driven trading firm at the forefront of systematic execution and quantitative research, operating across multiple asset classes and markets. They are now looking for a Senior Quantitative Developer to join a high-impact team responsible for building a next-generation alpha research platform.
This is not just another quant dev role; you will be working on the core infrastructure that powers alpha generation, from data ingestion and processing through to model evaluation, reporting, and deployment. The team is focused on solving complex problems around execution quality, market impact, and data-driven decision-making, using cutting-edge tools and large-scale datasets.
You will work closely with quants and researchers, influence architecture decisions, and play a key role in shaping how strategies are built and tested across the business.
Required Skills:
- Strong experience with Python (5+ years) in a quantitative finance environment
- Experience building data pipelines, research platforms or ML workflows
- Strong understanding of statistics, linear models & model evaluation techniques
- Experience with the Python data stack (NumPy, Pandas, etc.) and ML libraries
- Familiarity with tools such as PyTorch, TensorFlow, JAX, Plotly, Altair
- Experience working with large datasets and performance-sensitive systems
- Strong problem-solving ability with attention to detail
- Ability to communicate complex technical ideas clearly
Nice to have:
- Experience with C++, Rust or CUDA
- Experience optimising or debugging low-level performance in data/ML systems
Exclusive Benefits:
- £130,000 - £220,000 Base Salary + Bonus
- Work on core alpha research infrastructure, not peripheral systems
- Direct collaboration with quant researchers and trading teams
- High level of technical ownership and architectural influence
- Opportunity to mentor and lead within a high-performance team
- Access to large-scale datasets and cutting-edge tooling
- Clear progression into Lead Quant Dev / Platform Architect roles
- High-autonomy, low-politics, performance-driven culture
- Work in a team solving real, high-value quantitative problems
If you are a Quantitative Developer who wants to build core research infrastructure, work alongside top-tier quants, and have a direct impact on how trading strategies are developed and deployed, click APPLY NOW and attach your FULL CV and contact details for immediate consideration.
Quantitative Developer employer: Sterling Bridge Limited
Contact Detail:
Sterling Bridge Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Developer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get you in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, especially those related to quantitative finance. We want to see your problem-solving abilities and how you tackle complex data challenges.
✨Tip Number 3
Prepare for technical interviews by brushing up on your statistics and model evaluation techniques. We recommend practicing coding problems and discussing your thought process clearly, as communication is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Quantitative Developer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Quantitative Developer role. Highlight your Python experience and any relevant projects you've worked on that showcase your skills in quantitative finance. We want to see how you can contribute to our next-gen alpha platform!
Showcase Your Skills: Don’t just list your skills; demonstrate them! Include specific examples of how you've built data pipelines or worked with ML workflows. This helps us understand your hands-on experience and how you can tackle complex problems in our high-performance trading environment.
Communicate Clearly: When writing your application, keep it clear and concise. Use straightforward language to explain your technical expertise and how it relates to the role. We appreciate candidates who can communicate complex ideas simply, as this is key in our collaborative environment.
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. Don’t forget to attach your full CV and contact details for immediate consideration!
How to prepare for a job interview at Sterling Bridge Limited
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially in the context of quantitative finance. Be prepared to discuss your experience with libraries like NumPy and Pandas, and be ready to solve coding challenges that test your understanding of data pipelines and ML workflows.
✨Showcase Your Problem-Solving Skills
During the interview, highlight specific examples where you've tackled complex problems in a high-performance trading environment. Discuss how you approached these challenges, the tools you used, and the impact of your solutions on execution quality or model evaluation.
✨Communicate Clearly and Confidently
You’ll need to explain complex technical ideas to both quants and researchers. Practice articulating your thought process and solutions clearly. Use simple language to convey your points, ensuring that even non-technical stakeholders can grasp your insights.
✨Prepare for Technical Questions
Expect deep dives into statistics, linear models, and model evaluation techniques. Brush up on these topics and be ready to discuss how they apply to your previous work. Familiarise yourself with performance-sensitive systems and be prepared to talk about any experience you have with C++, Rust, or CUDA.