At a Glance
- Tasks: Develop and maintain quantitative models for credit analysis and investment strategies.
- Company: Leading London-based asset manager specialising in credit investing.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on innovation and automation.
- Why this job: Join a cutting-edge team and make an impact in global credit markets.
- Qualifications: Degree in a quantitative field and strong programming skills in Python.
The predicted salary is between 50000 - 70000 € per year.
Octavius Finance are a specialist hedge fund and asset management recruitment firm, working with leading investment managers across public and private markets. They are recruiting for a Credit Quantitative Researcher on behalf of a London-based asset manager specialising in credit investing, long/short credit strategies, and credit hedge fund investing across global credit markets, with a primary focus on European credit.
This Credit Quantitative Researcher role sits within a credit investment team covering corporate bonds, leveraged loans, and structured credit instruments such as CLOs.
Key Responsibilities:- Develop, implement, and maintain quantitative models for credit relative value, pricing, and risk analysis across cash and structured credit markets.
- Build factor-based and statistical models for credit spread dynamics, default risk, and recovery assumptions.
- Analyse large, complex datasets across corporate bonds, leveraged loans, CDS, and structured credit products (including CLO tranches).
- Support portfolio construction, optimisation, and trade idea generation across long/short credit strategies.
- Develop tools for risk monitoring, stress testing, scenario analysis, and performance attribution.
- Enhance pricing and valuation frameworks for illiquid or complex credit instruments.
- Work closely with portfolio managers and analysts to translate quantitative outputs into actionable investment insights.
- Contribute to automation and improvement of research workflows and data pipelines.
- Research and prototype new quantitative approaches for credit investing, including machine learning and alternative data applications.
- Degree in a highly quantitative discipline (e.g. mathematics, physics, engineering, statistics, computer science, finance, econometrics).
- Experience in credit markets, fixed income, or structured credit strongly preferred.
- Strong programming skills in Python (or equivalent), with experience in data analysis libraries (e.g. pandas, NumPy, SciPy).
- Good understanding of credit products including corporate bonds, leveraged loans, CDS, and CLO structures.
- Knowledge of statistical modelling, time series analysis, and machine learning techniques beneficial.
- Familiarity with risk modelling, portfolio construction, or quantitative trading strategies.
- Experience working with large financial datasets and building robust research pipelines.
- Strong analytical mindset with ability to work with incomplete or noisy financial data.
- Excellent communication skills and ability to work collaboratively within an investment team.
- Strong interest in global credit markets and alternative investment strategies.
To apply, please submit a copy of your word CV to quantresearch@octaviusfinance.com.
Long Short Systematic Credit Quantitative Researcher - London - Asset Manager employer: Octavius Finance
As a leading asset manager based in London, we pride ourselves on fostering a dynamic and inclusive work culture that encourages innovation and collaboration. Our commitment to employee growth is reflected in our comprehensive training programmes and opportunities for advancement within the firm, making us an excellent employer for those passionate about credit investing. Join us to be part of a forward-thinking team that values your contributions and supports your professional journey in the exciting world of global credit markets.
StudySmarter Expert Advice🤫
We think this is how you could land Long Short Systematic Credit Quantitative Researcher - London - Asset Manager
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend events, and connect on LinkedIn. We can’t stress enough how personal connections can open doors that applications alone can’t.
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills and understanding of credit markets. We recommend practising common quantitative problems and being ready to discuss your past projects in detail.
✨Tip Number 3
Showcase your passion for credit investing! When you get the chance to chat with potential employers, let them know why you’re excited about the role and how you can contribute to their team.
✨Tip Number 4
Don’t forget to apply through our website! It’s a great way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Long Short Systematic Credit Quantitative Researcher - London - Asset Manager
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of a Credit Quantitative Researcher. Highlight your experience in credit markets and any relevant quantitative skills. We want to see how your background aligns with the job description!
Showcase Your Skills:Don’t just list your programming skills; show us how you’ve used them! Include specific examples of projects where you’ve applied Python or data analysis libraries. This will help us understand 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:We encourage you to apply through our website for a smoother process. It helps us keep track of applications better and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Octavius Finance
✨Know Your Quantitative Stuff
Make sure you brush up on your quantitative skills, especially in areas like statistical modelling and machine learning. Be ready to discuss how you've applied these techniques in real-world scenarios, particularly in credit markets.
✨Showcase Your Programming Skills
Since strong programming skills in Python are a must, prepare to demonstrate your proficiency. Bring examples of projects where you've used data analysis libraries like pandas or NumPy to solve complex problems.
✨Understand the Credit Landscape
Familiarise yourself with various credit products such as corporate bonds, leveraged loans, and CLOs. Be prepared to discuss current trends in the credit market and how they might impact investment strategies.
✨Communicate Clearly
As you'll be working closely with portfolio managers and analysts, practice explaining complex quantitative concepts in simple terms. Good communication can set you apart, so think about how to convey your insights effectively.
