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- Tasks: Develop and maintain quantitative models for credit analysis and investment strategies.
- Company: Join a leading asset manager specialising in innovative credit investing.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborative team culture with a focus on innovation and automation.
- Why this job: Make an impact in global credit markets with cutting-edge quantitative research.
- 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.
Long Short Systematic Credit Quantitative Researcher – Asset Manager in Worcester employer: Octavius Finance
Contact Detail:
Octavius Finance Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Long Short Systematic Credit Quantitative Researcher – Asset Manager in Worcester
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend events, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Prepare for interviews by brushing up on your technical skills and understanding of credit markets. Practice common interview questions and be ready to discuss your quantitative models and how they apply to real-world scenarios.
✨Tip Number 3
Showcase your projects! If you've worked on relevant quantitative research or data analysis, make sure to highlight these in conversations. Bring along examples that demonstrate your skills and thought process.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take the initiative to engage with us directly.
We think you need these skills to ace Long Short Systematic Credit Quantitative Researcher – Asset Manager in Worcester
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 responsibilities outlined in the job description.
Showcase Your Skills: Don’t just list your programming skills; demonstrate them! Include specific examples of projects where you used Python or data analysis libraries. This helps us understand your practical experience and how you can contribute to our team.
Be Clear and Concise: When writing your application, clarity is key. Use straightforward language and avoid jargon unless it’s relevant to the role. We appreciate a well-structured application that makes it easy for us to see your qualifications.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy to do!
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 time series analysis. 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 in credit investing.
✨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 European credit market and how they might impact investment strategies.
✨Communicate Effectively
Since collaboration is key in this role, practice articulating your ideas clearly. Think about how you can translate complex quantitative outputs into actionable insights for portfolio managers and analysts during the interview.