Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop quantitative signals and trading strategies in single-name credit markets.
- Company: Leading global fund with a dynamic trading team in London.
- Benefits: Competitive salary, collaborative environment, and opportunities for professional growth.
- Other info: Join a fast-paced environment with excellent career advancement potential.
- Why this job: Make an impact on investment decisions while working with top professionals.
- Qualifications: 2-4 years in quantitative research or trading, strong Python skills required.
The predicted salary is between 60000 - 80000 £ per year.
A leading global fund is seeking a Quantitative Researcher to join its London trading team. This role focuses on developing quantitative signals and trading strategies in the single-name credit markets.
The ideal candidate will have 2-4 years of experience in quantitative research or front-office trading, with strong Python skills, especially in libraries like Pandas and NumPy.
This position offers the opportunity to work closely with Portfolio Managers and analysts, contributing to investment decisions and research infrastructure.
Quant Researcher – Single-Name Credit Signals in London employer: DURLSTON PARTNERS
Contact Detail:
DURLSTON PARTNERS Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Researcher – Single-Name Credit Signals in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working in quantitative research or trading. A friendly chat can open doors and give you insights that might just land you that interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, especially those using Pandas and NumPy. This not only demonstrates your technical abilities but also gives you something tangible to discuss during interviews.
✨Tip Number 3
Prepare for the technical grill! Brush up on your quantitative research concepts and be ready to tackle some coding challenges. Practising common interview questions can help you feel more confident when it’s your turn to shine.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace Quant Researcher – Single-Name Credit Signals in London
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your experience with Python, especially if you've worked with libraries like Pandas and NumPy. We want to see how you can leverage these tools in quantitative research, so don’t hold back!
Tailor Your Experience: When writing your application, focus on your 2-4 years of experience in quantitative research or front-office trading. We’re looking for specific examples that demonstrate your expertise and how it relates to the role.
Connect with Our Team: Mention any previous collaborations with Portfolio Managers or analysts in your application. We love seeing candidates who can work well in a team and contribute to investment decisions, so share those experiences!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team!
How to prepare for a job interview at DURLSTON PARTNERS
✨Know Your Quant Skills
Make sure you brush up on your quantitative research skills, especially in Python. Be ready to discuss your experience with libraries like Pandas and NumPy, and prepare to showcase how you've used them in past projects or roles.
✨Understand the Market
Familiarise yourself with the single-name credit markets. Research recent trends and developments, and be prepared to discuss how they might impact trading strategies. This shows your genuine interest and understanding of the role.
✨Prepare for Technical Questions
Expect technical questions that test your problem-solving abilities. Practice coding challenges or case studies related to quantitative analysis. We recommend using platforms like LeetCode or HackerRank to sharpen your skills before the interview.
✨Engage with Portfolio Managers
Since you'll be working closely with Portfolio Managers and analysts, think about how you can contribute to their decision-making process. Prepare thoughtful questions about their strategies and how your role fits into the bigger picture. This will demonstrate your collaborative mindset.