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- Tasks: Research and design innovative equity alpha signals for global markets.
- Company: Leading hedge fund with a focus on systematic research.
- Benefits: Competitive pay, performance bonuses, and comprehensive benefits package.
- Why this job: Make a real impact in finance with your research and ideas.
- Qualifications: Strong quantitative background and advanced Python skills required.
- Other info: Collaborative environment with opportunities for rapid idea implementation.
The predicted salary is between 36000 - 60000 £ per year.
This position offers the chance to join a systematic equities research function responsible for building and scaling differentiated alpha across global equity markets. The mandate is pure research: identifying new sources of equity alpha, validating them rigorously, and seeing successful ideas deployed with real capital. Researchers operate end-to-end, with ownership over data selection, signal design, testing, and ongoing performance evaluation. This is particularly well suited to researchers who already run live signals but want greater influence over the research agenda, cleaner decision-making, and a clearer line of sight between their work and outcomes.
Responsibilities:
- Researching, designing, and validating new systematic equity alpha signals across regions and time horizons
- Owning the full research lifecycle: data exploration, feature engineering, modelling, testing, and performance analysis
- Working closely with other senior researchers to combine signals into robust portfolios
- Contributing to portfolio construction and risk discussions, with clear visibility of live outcomes
- Leveraging an advanced research and execution stack built for speed, scale, and iteration
- Operating in a collaborative environment where good ideas move quickly into production
Experience:
- Strong academic foundation in a quantitative discipline (Mathematics, Physics, Computer Science, Engineering or similar)
- MSc or PhD from a leading university preferred
- Proven experience delivering live equity alpha in a buy-side or systematic trading environment
- Deep understanding of statistics, time-series analysis, and modern machine learning techniques
- Advanced Python skills for research and production-quality code
- Self-directed, intellectually honest, and motivated by research quality over noise
Compensation:
Competitive compensation with meaningful performance participation and full benefits.
McGregor Boyall is an equal opportunity employer and do not discriminate on any grounds.
Quantitative Researcher - Systematic Equities 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 - Systematic Equities in City of London
✨Tip Number 1
Network like a pro! Reach out to professionals in the hedge fund industry, especially those working in systematic equities. Attend meetups or webinars, and don’t be shy about asking for informational interviews. We all know that sometimes it’s not just what you know, but who you know!
✨Tip Number 2
Showcase your skills! Create a portfolio of your research projects, especially any live signals you've developed. This is your chance to shine and demonstrate your quantitative prowess. We recommend using platforms like GitHub to share your code and findings – it’s a great way to impress potential employers!
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Expect questions on statistics, time-series analysis, and machine learning techniques. We suggest doing mock interviews with friends or using online resources to practice. The more prepared you are, the more confident you’ll feel!
✨Tip Number 4
Apply through our website! We’ve got a streamlined application process that makes it easy for you to showcase your talents. Plus, it shows you’re genuinely interested in joining our team. Don’t miss out on the opportunity to land that dream job with us!
We think you need these skills to ace Quantitative Researcher - Systematic Equities in City of London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your quantitative skills and experience in your application. We want to see how you've used your knowledge in Mathematics, Physics, or Computer Science to deliver live equity alpha. Don't hold back on showcasing your advanced Python skills!
Tailor Your Application: Take the time to customise your application for the Quantitative Researcher role. Mention specific projects or experiences that align with our focus on systematic equities research. This shows us you're genuinely interested and have done your homework.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that get straight to the heart of your qualifications and experiences. Avoid fluff and make every word count!
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 makes it easier for us to keep track of all the amazing candidates like you!
How to prepare for a job interview at McGregor Boyall Associates Limited
✨Know Your Quantitative Stuff
Make sure you brush up on your quantitative skills, especially in statistics and machine learning. Be ready to discuss your previous research projects and how you've applied these techniques in real-world scenarios.
✨Showcase Your Coding Skills
Since advanced Python skills are a must, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice writing clean, efficient code that reflects your understanding of data manipulation and analysis.
✨Understand the Research Lifecycle
Familiarise yourself with the full research lifecycle from data selection to performance evaluation. Be prepared to discuss how you've owned this process in past roles and how you approach each stage to ensure high-quality outcomes.
✨Collaborate and Communicate
This role involves working closely with other researchers, so highlight your teamwork skills. Share examples of how you've collaborated on projects and contributed to discussions around portfolio construction and risk management.
