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- Tasks: Transform and enhance quantitative models using Python in a dynamic banking environment.
- Company: Leading global investment bank in the heart of London.
- Benefits: Competitive daily rate, potential for contract extension, and career growth opportunities.
- Other info: Opportunity to work with cutting-edge technology and expand your expertise across various asset classes.
- Why this job: Join a high-priority programme and make a real impact on modernising risk models.
- Qualifications: Strong Python skills and experience in credit risk or similar asset classes.
A leading global investment bank in the City of London is looking to hire a Quant Developer – Credit on a contract basis. This is an initial 6 month contract with the option to extend, paying a day rate in the region of £800 to £925 per day.
This role sits within a Quantitative Analytics function, initially aligned to a credit focused programme supporting the development and improvement of risk models. The focus is on modernising existing models and improving how they are built, structured and maintained, rather than pure front office pricing. The business is going through a broader modernisation programme and is looking for someone to play a key role in that transition. There is also scope to gain exposure to other asset classes and areas of the business over time, as well as the opportunity to move into a permanent role if of interest.
Key responsibilities- Redevelop and translate existing quantitative models into Python
- Improve model structure, performance and maintainability
- Work closely with quants and risk teams to understand model logic and outputs
- Support testing, validation and deployment into production
- Contribute to development best practices, including version control and testing
- Strong Python development experience within a quant or risk environment
- Experience working with credit risk, fixed income or similar asset classes
- Good understanding of econometrics or time series modelling
- Experience working within financial services, ideally banking
- Comfortable working across the full development lifecycle
- Experience working with or translating R code
- Exposure to C++ or working within mixed technology environments
- Front office or desk facing exposure working with quants or traders
- Knowledge of derivatives, XVA or broader risk modelling
- Experience working with modern data platforms or cloud environments
This is a strong opportunity to join a well-established team working on a high priority programme within a global bank, with scope to broaden your exposure beyond credit over time. If you are a Quant Developer with the above experience, please respond with an up-to-date CV.
Quant Developer - Credit in London employer: McCabe & Barton
Contact Detail:
McCabe & Barton Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Developer - Credit in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the finance and tech sectors. Attend meetups or webinars related to quantitative development and credit risk. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, especially those related to quantitative models or risk analysis. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with econometrics, time series modelling, and any relevant projects. Practice coding challenges that focus on Python and quantitative analysis.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be perfect for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Quant Developer - Credit in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Quant Developer role. Highlight your Python development experience and any relevant work with credit risk or similar asset classes. We want to see how your skills align with what we're looking for!
Showcase Your Projects: Include specific projects where you've redeveloped quantitative models or improved their structure and performance. This gives us a clear picture of your hands-on experience and how you can contribute to our modernisation programme.
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points for key achievements and avoid jargon unless it's relevant. We appreciate straightforward communication that gets to the heart of your qualifications.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved.
How to prepare for a job interview at McCabe & Barton
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially in the context of quantitative modelling. Be prepared to discuss specific projects where you've redeveloped models or improved performance, as this will show your practical experience.
✨Understand Credit Risk Fundamentals
Familiarise yourself with credit risk concepts and how they relate to the role. Be ready to explain how you've applied econometrics or time series modelling in past roles, as this knowledge will be crucial for the interview.
✨Showcase Your Collaboration Skills
Since you'll be working closely with quants and risk teams, highlight any past experiences where teamwork was key to your success. Prepare examples that demonstrate your ability to communicate complex ideas clearly and effectively.
✨Be Ready for Technical Questions
Expect technical questions related to model structure, testing, and deployment. Brush up on best practices in development, including version control and testing methodologies, so you can confidently discuss how you ensure quality in your work.