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- Tasks: Develop cutting-edge quantitative credit models and enhance alpha research.
- Company: Global asset manager with a strong focus on systematic credit capabilities.
- Benefits: Competitive salary and opportunities for professional growth.
- Other info: Collaborative environment with opportunities to engage across disciplines.
- Why this job: Make a real impact in finance by working on innovative credit models.
- Qualifications: BSc/MSc in a quantitative field and experience in building financial models.
The predicted salary is between 60000 - 80000 £ per year.
Our client is a global asset manager with a leading systematic credit capability. They seek a Quantitative Analyst to enhance alpha research, modelling and the research platform across investment grade, high yield and structured products. The role blends research, implementation and close partnership with portfolio teams.
Responsibilities
- Develop quantitative credit models, including spread and default risk frameworks.
- Source, test and integrate new alpha signals across credit markets into research pipelines.
- Monitor model-generated trade ideas and disseminate outputs to investment teams.
- Produce rigorous standalone research with clear reports and presentations.
- Contribute thematic quantitative research and thought leadership across credit.
- Build and maintain the research platform and shared analytical codebase.
- Improve communication and visualisation of model outputs for portfolio teams.
- Uphold code quality, version control and systematic testing standards.
- Translate quantitative insights for Portfolio Managers, Credit Analysts, Traders and Investment Directors.
- Engage in cross-asset forums and collaborate across regions and disciplines.
- Support the internal and external profile of the quantitative research function.
- Discuss model methodology and research outputs with clients when required.
Requirements
- BSc/MSc in a quantitative discipline; strong statistics, econometrics and numerical methods.
- Proven track record building quantitative models in an investment or credit context.
- Strong Python (pandas, NumPy); SQL and Git advantageous.
- Advanced Excel; familiarity with Bloomberg or similar data platforms.
- Experience handling large, complex financial datasets.
- Clear written and verbal communication of technical concepts.
- Collaborative and adaptable, comfortable working across functions and asset classes.
Quantitative Analyst – Credit, Global Asset Manager in London employer: Logansinclair
Contact Detail:
Logansinclair Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Analyst – Credit, Global Asset Manager in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend events, and connect 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 quantitative skills and understanding the latest trends in credit markets. Practice explaining complex concepts in simple terms – it’ll impress the interviewers!
✨Tip Number 3
Showcase your projects! If you've built any models or conducted research, be ready to discuss them in detail. Bring along reports or presentations to demonstrate your analytical prowess.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Quantitative Analyst – Credit, Global Asset Manager in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Quantitative Analyst role. Highlight your experience with quantitative models, Python, and any relevant projects that showcase your skills in credit analysis. We want to see how you fit into our world!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about quantitative analysis and how your background aligns with our needs. Be sure to mention any specific experiences that relate to the responsibilities listed in the job description.
Showcase Your Technical Skills: Don’t forget to highlight your technical skills, especially in Python, SQL, and Excel. If you've worked with large datasets or have experience in model development, make that clear! We love seeing candidates who can demonstrate their technical prowess.
Apply Through Our Website: We encourage you to apply through our website for a smoother application 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 Logansinclair
✨Know Your Models Inside Out
Make sure you can discuss the quantitative credit models you've built in detail. Be prepared to explain your methodology, the challenges you faced, and how you overcame them. This shows your depth of knowledge and problem-solving skills.
✨Brush Up on Your Python Skills
Since strong Python skills are crucial for this role, practice coding problems related to data manipulation and analysis. Familiarise yourself with libraries like pandas and NumPy, and be ready to demonstrate your coding abilities during the interview.
✨Prepare for Technical Questions
Expect questions that test your understanding of statistics, econometrics, and numerical methods. Review key concepts and be ready to apply them to real-world scenarios, especially in the context of credit risk and investment strategies.
✨Communicate Clearly and Confidently
You’ll need to translate complex quantitative insights for various stakeholders. Practice explaining your research and findings in simple terms, and prepare to discuss how you would improve communication and visualisation of model outputs for portfolio teams.