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- Tasks: Develop and implement models for asset-liability forecasting and interest rate risk management.
- Company: Join a leading global financial institution with a strong reputation in the finance sector.
- Benefits: Enjoy competitive pay, potential remote work options, and opportunities for professional growth.
- Why this job: Make a real impact in finance while working with cutting-edge statistical techniques and technology.
- Qualifications: Strong background in ALM or Treasury modelling, Python skills, and excellent communication abilities required.
- Other info: This role is based in London and offers a chance to work with a dynamic team.
The predicted salary is between 48000 - 72000 £ per year.
We’re working with a leading global financial institution seeking an experienced ALM Quantitative Analyst (AVP level) to join their Treasury Quantitative Analytics team in London. This is a high-impact role supporting Treasury Finance by developing statistical models to forecast behavioural asset and liability balances—key to managing interest rate risk.
Key Responsibilities:- Develop and implement quantitative models for asset-liability forecasting and interest rate risk management.
- Utilise advanced econometric and statistical techniques such as time series analysis and regression modelling.
- Translate complex technical concepts for both technical and non-technical stakeholders.
- Write robust, production-ready Python code and partner with technology teams to operationalise models.
- Ensure models are compliant with internal governance and model risk frameworks.
- Provide ongoing model validation, documentation, and performance monitoring.
- Strong background in ALM or Treasury modelling, particularly behavioural balance forecasting.
- Deep knowledge of statistical/econometric methods.
- Solid Python programming skills and experience handling large datasets.
- Clear and confident communicator, able to bridge the technical and business gap.
Quantitative Analyst employer: Radley James
Contact Detail:
Radley James Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Analyst
✨Tip Number 1
Familiarise yourself with the latest trends in asset-liability management (ALM) and interest rate risk. This will not only help you understand the role better but also allow you to engage in informed discussions during interviews.
✨Tip Number 2
Brush up on your Python programming skills, especially focusing on libraries like Pandas and NumPy that are essential for handling large datasets. Being able to demonstrate your coding proficiency can set you apart from other candidates.
✨Tip Number 3
Prepare to explain complex statistical concepts in simple terms. Since the role requires translating technical jargon for non-technical stakeholders, practice how you would communicate these ideas clearly and effectively.
✨Tip Number 4
Network with professionals in the finance and quantitative analysis sectors. Attend relevant meetups or webinars to connect with industry insiders who might provide insights or even referrals for the position.
We think you need these skills to ace Quantitative Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in ALM or Treasury modelling, particularly in behavioural balance forecasting. Use specific examples that demonstrate your knowledge of statistical and econometric methods.
Craft a Compelling Cover Letter: In your cover letter, explain why you are interested in the Quantitative Analyst position and how your skills align with the job requirements. Emphasise your Python programming skills and your ability to communicate complex concepts clearly.
Showcase Your Technical Skills: If you have experience with time series analysis, regression modelling, or handling large datasets, make sure to include this in your application. Consider providing examples of projects where you successfully applied these techniques.
Proofread Your Application: Before submitting your application, carefully proofread all documents for spelling and grammatical errors. A polished application reflects your attention to detail, which is crucial for a role that involves developing robust models.
How to prepare for a job interview at Radley James
✨Showcase Your Technical Skills
Be prepared to discuss your experience with statistical models and Python programming. Bring examples of your past work, especially any relevant projects involving asset-liability forecasting or interest rate risk management.
✨Communicate Clearly
Since the role requires translating complex concepts for various stakeholders, practice explaining your technical knowledge in simple terms. This will demonstrate your ability to bridge the gap between technical and non-technical audiences.
✨Understand the Company’s Needs
Research the financial institution and its Treasury Quantitative Analytics team. Familiarise yourself with their current challenges and how your skills can help address them, particularly in model validation and compliance.
✨Prepare for Technical Questions
Expect questions on econometric techniques and model development. Brush up on time series analysis and regression modelling, and be ready to discuss how you would apply these methods in real-world scenarios.
