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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 salary, potential remote work options, and opportunities for professional growth.
- Why this job: Make a real impact in Treasury Finance while working with advanced statistical techniques and a dynamic team.
- 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 on high-impact projects.
The predicted salary is between 54000 - 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. Understanding current market conditions and how they affect forecasting will help you stand out during discussions with the hiring team.
✨Tip Number 2
Brush up on your Python skills, especially in relation to data handling and model implementation. Consider working on personal projects or contributing to open-source projects that showcase your ability to write production-ready code.
✨Tip Number 3
Prepare to explain complex statistical concepts in simple terms. Practising how to communicate these ideas clearly will be crucial, as you'll need to bridge the gap between technical and non-technical stakeholders.
✨Tip Number 4
Network with professionals in the finance and quantitative analysis sectors. Attend relevant meetups or webinars to connect with others in the field, which could lead to valuable insights and potential referrals for the role.
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 Communication Skills: Since the role requires translating complex concepts for various stakeholders, include examples in your application that demonstrate your ability to communicate technical information clearly and effectively.
Tailor Your Application: Customise your CV and cover letter to reflect the specific requirements mentioned in the job description. Use keywords related to econometric methods, model validation, and performance monitoring to catch the employer's attention.
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 production-ready code. You might even want to prepare a brief coding exercise to showcase your ability to handle large datasets effectively.
✨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 be ready to provide examples of how you've successfully communicated technical information in the past.
✨Understand Governance and Compliance
Familiarise yourself with internal governance and model risk frameworks relevant to the financial industry. Be prepared to discuss how you ensure compliance in your modelling work and any experiences you have with model validation and performance monitoring.
