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- Tasks: Collaborate with investment pros to turn ideas into actionable analytics and enhance research frameworks.
- Company: A leading buy-side investment platform with a focus on innovation and collaboration.
- Benefits: Highly competitive salary, performance bonuses, and comprehensive benefits package.
- Why this job: Make a real impact in a dynamic environment while working on complex, multi-asset strategies.
- Qualifications: Strong Python programming skills and experience in quantitative research or trading.
- Other info: Flexible role with opportunities for growth and learning in a fast-paced industry.
The predicted salary is between 48000 - 72000 £ per year.
A well-established buy-side investment platform is looking to add a Quantitative Researcher to a desk-facing environment supporting complex, multi-asset strategies with a strong credit bias. The role is intentionally flexible on level and suited to someone who enjoys working close to investment decision-making - translating market intuition and trade ideas into robust, scalable quantitative frameworks. The emphasis is on practical research, not academic isolation.
Responsibilities:
- Act as a quantitative partner to senior investment professionals, helping turn ideas into actionable analytics
- Enhance and evolve internal research frameworks used to analyse relative value, risk, and pricing across complex instruments
- Build reusable research components and libraries that support both discretionary and systematic approaches
- Explore new datasets, methodologies, and signals to improve trade selection and portfolio construction
- Stress-test ideas through structured analysis rather than one-off experiments
- Improve the reliability, speed, and usability of existing research workflows
- Contribute to longer-term projects focused on scaling quantitative insight across strategies
- Share findings clearly, whether through code, written summaries, or discussion with stakeholders
Experience:
- Strong programming capability in Python; additional low-level or performance-focused experience welcomed
- Background in a quantitative research, trading, or analytics role within a professional investment environment
- Advanced academic training in a numerate discipline
- Familiarity with fixed income or credit-style instruments helpful, but depth in one area valued over broad exposure
- Comfortable working with ambiguity and evolving priorities
Compensation:
Highly competitive base salary with performance-linked bonus and comprehensive benefits.
Quantitative Researcher- Cross-Asset Relative Value in City of London employer: McGregor Boyall Associates Limited
Contact Detail:
McGregor Boyall Associates Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher- Cross-Asset Relative Value in City of London
✨Tip Number 1
Network like a pro! Reach out to professionals in the hedge fund space, especially those who work with quantitative research. Use platforms like LinkedIn to connect and engage with them; you never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your programming projects in Python or any relevant quantitative analyses you've done. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss how you've tackled complex data challenges in the past and how you can apply that to their investment strategies.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are proactive and genuinely interested in joining our team. Plus, it makes it easier for us to keep track of your application!
We think you need these skills to ace Quantitative Researcher- Cross-Asset Relative Value in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Quantitative Researcher role. Highlight your programming skills in Python and any relevant experience in quantitative research or trading. We want to see how you can contribute to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about quantitative research and how your background makes you a great fit for the role. Don’t forget to mention your interest in working closely with investment professionals.
Showcase Your Analytical Skills: In your application, demonstrate your analytical mindset. Share examples of how you've tackled complex problems or improved workflows in previous roles. We love seeing candidates who can think critically and adapt to evolving priorities!
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’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at McGregor Boyall Associates Limited
✨Know Your Quantitative Stuff
Make sure you brush up on your quantitative research skills, especially in Python. Be ready to discuss your past projects and how you've applied your programming skills to solve real-world problems. This role is all about practical application, so show them you can translate theory into actionable insights.
✨Understand the Market Landscape
Familiarise yourself with the current trends in the hedge fund industry, particularly around cross-asset strategies and credit instruments. Being able to discuss recent market movements or relevant datasets will demonstrate your engagement and understanding of the field.
✨Prepare for Problem-Solving Questions
Expect to tackle some scenario-based questions that test your analytical thinking. Think about how you would approach stress-testing ideas or improving existing workflows. Practising these types of questions can help you articulate your thought process clearly during the interview.
✨Communicate Clearly and Confidently
Since you'll be working closely with senior investment professionals, it's crucial to convey your findings effectively. Practice summarising complex ideas in simple terms, whether through code explanations or discussions. Clear communication can set you apart from other candidates.
