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- Tasks: Analyse assets and data, build forecasting models, and support investment decisions.
- Company: Join a dynamic private credit fund based in London, focused on asset-backed credit.
- Benefits: Enjoy competitive pay, potential remote work options, and a collaborative team environment.
- Why this job: Be part of a cutting-edge team making impactful investment decisions in a fast-paced industry.
- Qualifications: Advanced degree in a quantitative field and 4-8 years of relevant experience required.
- Other info: Experience with retail banks or credit risk is a plus!
The predicted salary is between 54000 - 84000 £ per year.
Our client, a London based private credit fund is seeking a Senior Associate/Vice President to join their asset-backed credit team in London.
You will:
- Perform in-depth asset and data analysis and build models to forecast future asset performance and behaviours to support investment theses using SQL and Python.
- Drive due diligence processes, coordinating inputs from legal, technical, and commercial advisors.
- Support thematic research and opportunity mapping across asset classes and jurisdictions.
You'll need:
- A strong academic background, ideally with an advanced degree in a quantitative or analytical field (e.g. Engineering, Maths, Physics, Economics, or similar).
- 4–8 years of experience of i) working with large data sets and building forecasting models and ii) using the outputs to make business or investment decisions.
- Experience working within or closely with a retail bank (particularly in credit risk), asset-backed finance, NPL investment firms/ funds, structured lending or data-driven lending models, is highly advantageous.
Credit Risk Quant (ABF) employer: RCQ Associates - Financial Markets Specialists
Contact Detail:
RCQ Associates - Financial Markets Specialists Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Credit Risk Quant (ABF)
✨Tip Number 1
Familiarise yourself with the latest trends in asset-backed finance and credit risk management. This knowledge will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Network with professionals in the industry, especially those working in private credit funds or retail banks. Attend relevant events or webinars to make connections that could lead to referrals or insider information about the role.
✨Tip Number 3
Brush up on your SQL and Python skills, as these are crucial for the role. Consider working on personal projects or contributing to open-source projects to showcase your abilities in data analysis and model building.
✨Tip Number 4
Prepare to discuss specific examples from your past experience where you've successfully built forecasting models or made data-driven decisions. Being able to articulate your contributions clearly will set you apart from other candidates.
We think you need these skills to ace Credit Risk Quant (ABF)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in credit risk, asset-backed finance, and data analysis. Use specific examples that demonstrate your ability to work with large data sets and build forecasting models.
Craft a Strong Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention your academic background and how it aligns with the job requirements. Highlight your experience in coordinating due diligence processes and thematic research.
Showcase Technical Skills: Emphasise your proficiency in SQL and Python within your application. Provide examples of how you've used these tools in previous roles to support investment decisions or model asset performance.
Highlight Relevant Experience: Clearly outline your 4-8 years of experience in the field. If you have worked closely with retail banks or in credit risk, make sure to detail this experience and how it has prepared you for the role.
How to prepare for a job interview at RCQ Associates - Financial Markets Specialists
✨Showcase Your Analytical Skills
Be prepared to discuss your experience with large data sets and forecasting models. Highlight specific projects where you used SQL and Python to derive insights, as this will demonstrate your technical proficiency and analytical mindset.
✨Understand the Asset-Backed Credit Landscape
Research the current trends in asset-backed finance and credit risk. Being knowledgeable about recent developments in the industry will show your genuine interest and help you engage in meaningful discussions during the interview.
✨Prepare for Technical Questions
Expect questions that test your understanding of credit risk and data analysis. Brush up on key concepts and be ready to explain how you've applied them in your previous roles, especially in relation to investment decisions.
✨Demonstrate Team Collaboration
Since the role involves coordinating with various advisors, be ready to share examples of how you've successfully worked in teams. Emphasise your communication skills and ability to collaborate across different functions to achieve common goals.
