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For Companies At a Glance
- 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 by supporting Treasury Finance and enhancing your quantitative skills in a dynamic environment.
- Qualifications: Strong background in ALM or Treasury modelling, Python programming, and statistical methods required.
- Other info: Ideal for those looking to bridge technical and business communication in a high-impact role.
The predicted salary is between 60000 - 84000 £ 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.
Ideal Candidate Will Have:
- 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 in relation to statistical modelling and data handling. Consider working on personal projects or contributing to open-source projects that showcase your ability to write robust, production-ready code.
✨Tip Number 3
Prepare to explain complex technical concepts in simple terms. Practice translating your past experiences into relatable stories that demonstrate your ability to communicate effectively with both technical and non-technical stakeholders.
✨Tip Number 4
Network with professionals in the financial sector, particularly those involved in Treasury and ALM roles. Attend industry events or join relevant online forums to gain insights and potentially get referrals for the position.
We think you need these skills to ace Quantitative Analyst
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities of a Quantitative Analyst in Treasury. Familiarise yourself with asset-liability management and interest rate risk concepts to tailor your application effectively.
Highlight Relevant Experience: In your CV and cover letter, emphasise your experience with ALM modelling and statistical techniques. Provide specific examples of projects where you've developed quantitative models or used Python for data analysis.
Showcase Technical Skills: Make sure to detail your Python programming skills and any experience with large datasets. Mention any relevant tools or libraries you’ve used, such as Pandas or NumPy, to demonstrate your technical proficiency.
Communicate Clearly: Since the role requires translating complex concepts for various stakeholders, ensure your application reflects your ability to communicate clearly. Use straightforward language and avoid jargon where possible to showcase this skill.
How to prepare for a job interview at Radley James
✨Showcase Your Technical Skills
Be prepared to discuss your experience with statistical models and econometric techniques. Highlight specific projects where you've developed models for asset-liability forecasting or interest rate risk management, and be ready to explain the methodologies you used.
✨Demonstrate Python Proficiency
Since solid Python programming skills are crucial for this role, consider bringing examples of your code or discussing past projects where you wrote production-ready code. Be ready to answer technical questions about your coding practices and how you handle large datasets.
✨Communicate Clearly
As a Quantitative Analyst, you'll need to bridge the gap between technical and non-technical stakeholders. Practice explaining complex concepts in simple terms, and prepare to give examples of how you've successfully communicated technical information in previous roles.
✨Understand Governance and Compliance
Familiarise yourself with model risk frameworks and internal governance processes. Be prepared to discuss how you've ensured compliance in your previous work, and think about how you would approach model validation and performance monitoring in this new role.
