At a Glance
- Tasks: Migrate risk model code from R to Python and enhance credit banking models.
- Company: Global financial institution known for innovation and strong regulatory discipline.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with potential for cross-team projects and career advancement.
- Why this job: Join a dynamic team and make a real impact in quantitative risk management.
- Qualifications: Strong Python programming skills and a solid foundation in econometrics required.
The predicted salary is between 48000 - 72000 £ per year.
Location: London, Hybrid
About the Company
Our client is a prominent global financial institution operating across multiple markets, offering investment banking, corporate banking and risk management services. Known for its strong regulatory discipline and commitment to innovation, the firm maintains robust infrastructure and technology teams that support critical quantitative, risk and analytics functions across its international operations.
Job Description
The Quantitative Analytics team within the investment banking division is seeking a skilled and motivated Credit Quant Developer to support a high‑priority migration of risk model code. This role focuses on quantitative risk (Market, Credit and Interest Rate Risk) rather than front‑office pricing, and plays a vital part in enhancing the stability and adaptability of the firm's credit banking book models. You will be responsible for translating and restructuring existing model components, primarily migrating code from R to Python - ensuring the newly implemented versions are efficient, well‑organised and maintainable. This role requires strong technical ability, excellent problem solving skills and a solid foundation in econometrics and time‑series methodologies.
Key Responsibilities:
- Lead the migration and translation of quantitative model code, focusing heavily on transitioning existing R models into Python.
- Develop and implement clean, logical and scalable code structures that can be easily adapted to evolving business and regulatory needs.
- Apply strong econometric knowledge to handle model challenges, identifying improved coding solutions when direct translation is not suitable.
- Work collaboratively within the Credit QA team to produce well‑documented, thoroughly tested and production‑ready model code.
Ideal Qualifications
- Strong programming ability in Python, including experience using GIT or similar version‑control tools.
- Solid understanding of econometrics, including foundational concepts such as linear regression, time‑series analysis and factor analysis.
- Experience working within the banking or broader financial services sector, ideally within a regulated environment.
- A critical, analytical mindset with the ability to review and challenge model behaviour and code quality.
Nice to have
- Familiarity with R / R‑Studio or the ability to comfortably interpret R code, which supports the migration process.
- Understanding of C++ for potential cross‑team collaboration.
- Exposure to quantitative risk domains including Market Risk, Credit Risk or Interest Rate Risk.
- Advanced econometric knowledge, such as experience with capital models, meta‑models or correlation modelling.
Quantitative Developer in London employer: Glocomms
As a leading global financial institution based in London, our client offers an exceptional work environment that fosters innovation and collaboration within the Quantitative Analytics team. Employees benefit from a hybrid work model, competitive remuneration, and opportunities for professional growth, all while contributing to critical projects that enhance the firm's risk management capabilities. The company's commitment to regulatory discipline and cutting-edge technology ensures that team members are at the forefront of the financial services industry, making it an ideal place for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Developer in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the finance and tech sectors on LinkedIn. Join relevant groups, attend meetups, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a GitHub repository showcasing your Python projects, especially those related to quantitative analysis or risk modelling. This gives potential employers a tangible look at what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your econometrics and coding skills. Practice common coding challenges and be ready to discuss your thought process. We recommend using platforms like LeetCode or HackerRank to sharpen your skills.
✨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 and engaged with our company. So, get that application in and let’s make it happen!
We think you need these skills to ace Quantitative Developer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Quantitative Developer role. Highlight your programming skills in Python and any experience with R, as well as your understanding of econometrics. We want to see how your background fits with our needs!
Showcase Your Projects:Include any relevant projects or experiences that demonstrate your coding abilities and problem-solving skills. If you've worked on migrating code or developing models, let us know! This will help us see your practical experience.
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 shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Glocomms
✨Know Your Code Inside Out
Make sure you’re comfortable with both R and Python, as you'll be discussing the migration of models. Brush up on your coding skills and be ready to explain your thought process behind translating code from one language to another.
✨Brush Up on Econometrics
Since the role requires a solid understanding of econometrics, review key concepts like linear regression and time-series analysis. Be prepared to discuss how these concepts apply to risk modelling and how you’ve used them in past projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of challenges you've faced in coding or model development. Highlight how you approached these problems and the solutions you implemented, especially in a regulated environment.
✨Collaborate and Communicate
This role involves working closely with the Credit QA team, so demonstrate your ability to collaborate. Think of examples where you’ve worked in a team setting, focusing on how you communicated complex ideas clearly and effectively.
