Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Join a dynamic team to develop and deploy cutting-edge risk models using Python.
- Company: Innovative financial firm with a collaborative and inclusive culture.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Why this job: Make a real impact in finance while working with advanced technologies and methodologies.
- Qualifications: 3 years of Python experience in data or risk roles; solid SQL skills required.
- Other info: Collaborative environment with a focus on continuous improvement and learning.
The predicted salary is between 48000 - 72000 £ per year.
About the team
You will join a small, London based Financial Risk team that designs, develops and deploys risk models covering credit, market, capital and liquidity for derivative trading. The group works closely with Model Validation, Regulatory Capital, Finance, Treasury, Credit Operations, Enterprise Data and Technology. The environment is cross‐functional, commercially focused, and hybrid (typically three days on site).
Role purpose
Help build, maintain and productionise quantitative risk models and the surrounding automation so the business can act quickly on high‐quality risk insights. You will contribute code, testing, documentation and operational run‐books, and support incremental migrations toward cloud tooling.
What you will do
- Contribute to the design, development and deployment of Python‐based risk models (e.g., components of VaR/ES or PD/LGD pipelines) under senior guidance.
- Refactor and harden existing code paths; add unit tests, data validation checks and logging.
- Build and maintain CI/CD jobs in GitLab for model rebuilds and scheduled tasks; assist with release notes and rollbacks.
- Automate recurring processes and controls (data loads, reconciliations, report generation).
- Collaborate with first‐line commercial teams to clarify requirements and triage model output questions.
- Support early cloud migration tasks (e.g., packaging jobs, testing connectors, basic Looker dashboards) with mentorship from seniors.
Tech you will use
- Python (pandas, NumPy; matplotlib for basic plots) and SQL for model development and analysis.
- GitLab for source control and deployment pipelines.
- Exposure to MongoDB and GCP services; growing use of Looker and Vertex AI as the stack transitions.
What you will learn/exposure
- Industry‐standard risk modelling concepts (stress testing, VaR/ES, PD/LGD).
- Model lifecycle & controls (documentation, validation, monitoring, and auditability).
- Stakeholder engagement across risk, finance, treasury, capital & tech.
Minimum requirements (aimed at ~3 years' experience)
- ~3 years with Python in a data or risk/quant adjacent role, including pandas/NumPy and writing testable, readable code.
- Solid SQL for data wrangling and reconciliation.
- Practical Git experience; familiarity with GitLab or similar CI/CD.
- Understanding of at least one risk domain (market, credit, capital or liquidity) and basic knowledge of common models (e.g., VaR/ES or PD/LGD).
- Comfortable working in a hybrid, collaborative setup with clear, concise communication.
Nice-to-have
- Experience in a bank/consultancy risk team or adjacent regulated environment.
- Exposure to MongoDB, GCP, Looker, or Vertex AI.
- Familiarity with model monitoring/alerting and data quality frameworks.
Ways of working & culture
We value ownership, pace, client focus, and raising the bar while staying collaborative and inclusive. Team members are encouraged to think big, automate where possible, and ship improvements continuously. Hybrid working with three days in the office supports collaboration and learning.
AVP - Python Quant Developer - Risk in London employer: Barclay Simpson
Contact Detail:
Barclay Simpson Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AVP - Python Quant Developer - Risk in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a GitHub repository with some of your Python projects or risk models. This gives potential employers a taste of what you can do and makes you stand out.
✨Tip Number 3
Prepare for interviews by brushing up on common risk modelling concepts. Be ready to discuss your experience with Python, SQL, and any relevant tools like GitLab. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace AVP - Python Quant Developer - Risk in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, SQL, and any relevant risk modelling concepts. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about risk modelling and how your background makes you a great fit for our team. Keep it concise but impactful!
Showcase Your Projects: If you've worked on any relevant projects, whether in a professional or personal capacity, make sure to mention them. We love seeing practical examples of your coding skills and problem-solving abilities!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re keen on joining our team!
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 how you've used these tools in past projects, particularly in risk modelling or data analysis.
✨Understand Risk Modelling Concepts
Familiarise yourself with key risk concepts such as VaR/ES and PD/LGD. Be prepared to explain these models and how they apply to the role, as well as any experience you have in these areas.
✨Showcase Your CI/CD Knowledge
Since the role involves building and maintaining CI/CD jobs in GitLab, be ready to talk about your experience with version control and deployment pipelines. Highlight any specific projects where you've implemented these practices.
✨Communicate Clearly and Collaboratively
Given the cross-functional nature of the team, practice articulating your thoughts clearly. Think of examples where you've successfully collaborated with different teams, and be ready to discuss how you handle feedback and requirements.
