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- Tasks: Design and enhance financial risk models using Python in a dynamic team.
- Company: Join a leading FTSE-listed financial services firm in London.
- Benefits: Hybrid work model, competitive salary, and exposure to senior stakeholders.
- Why this job: Take ownership of impactful projects and develop your skills in a modern tech environment.
- Qualifications: Strong Python skills and experience in financial risk modelling required.
- Other info: Collaborative team with opportunities for growth and cloud migration involvement.
The predicted salary is between 43200 - 72000 ÂŁ per year.
Barclay Simpson is partnering with a leading FTSE-listed financial services firm to hire a Senior Python Risk Quantitative Analyst into its London-based Financial Risk team. This is a high-impact opportunity within a visible, technically strong function responsible for the firm’s market, credit, capital and liquidity risk models. The role offers direct exposure to senior stakeholders and genuine ownership of model development.
What you’ll be doing:
- Designing and enhancing Market Risk models (VaR, Expected Shortfall, stress testing)
- Contributing to Credit Risk model development (wholesale / traded exposure preferred)
- Rebuilding and optimising existing quantitative models
- Developing and deploying production-quality Python code
- Supporting automation and model lifecycle improvements
- Working closely with Validation, Regulatory Capital, Finance and Technology teams
- Contributing to ongoing cloud migration (GCP environment)
What we’re looking for:
- Strong Python (Pandas, NumPy; production-level code)
- Solid experience developing financial risk models within:
- A bank
- Broker / trading firm
- Risk consultancy
- VaR
- Expected Shortfall
- Stress testing
- LGD / PD frameworks
The Environment:
- London-based (hybrid – 3 days office)
- Lean, high-visibility team
- Strong interaction with senior leadership
- Modern tech stack (Python, SQL, Git-based deployment, cloud transition underway)
If you’re looking for a role with genuine ownership and breadth — rather than a siloed “factory” environment — this could be an excellent next step.
Message Scott Nye at Barclay Simpson for a confidential discussion.
Senior Python Risk Quantitative Analyst in City of London employer: Barclay Simpson
Contact Detail:
Barclay Simpson Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Python Risk Quantitative Analyst in City of London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work at firms you're interested in. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Prepare for interviews by brushing up on your Python skills and financial risk concepts. Be ready to discuss your past projects and how they relate to market and credit risk models. Confidence is key!
✨Tip Number 3
Showcase your problem-solving skills during interviews. Think of examples where you've optimised models or improved processes. This will demonstrate your commercial mindset and ability to deliver results.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Python Risk Quantitative Analyst in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Python Risk Quantitative Analyst role. Highlight your experience with financial risk models and Python coding, especially if you've worked in a bank or trading firm. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include specific projects where you've designed or enhanced risk models. If you've worked on VaR or stress testing, let us know! This will help us understand your hands-on experience and how you can contribute to our team.
Communicate Clearly: Since you'll be engaging with non-technical stakeholders, make sure your application reflects your ability to communicate complex ideas simply. We appreciate clear and concise language that shows you can bridge the gap between technical and non-technical teams.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates. Plus, it’s super easy!
How to prepare for a job interview at Barclay Simpson
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially with libraries like Pandas and NumPy. Be ready to discuss your experience with production-level code and how you've used these tools in developing financial risk models.
✨Understand Financial Risk Models
Familiarise yourself with key concepts such as VaR, Expected Shortfall, and stress testing. Be prepared to explain how you've contributed to model development in previous roles, particularly in a banking or trading environment.
✨Communicate Clearly with Non-Technical Stakeholders
Since the role involves engaging with senior stakeholders, practice explaining complex technical concepts in simple terms. Think of examples where you've successfully communicated your ideas to non-technical audiences.
✨Showcase Your Commercial Mindset
Be ready to discuss how you balance modelling rigour with delivery pace. Share examples of how you've made decisions that reflect a strong understanding of business needs while maintaining technical excellence.