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- Tasks: Research and design innovative equity Alpha signals for global markets.
- Company: Dynamic 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 career growth.
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 life cycle: 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.
Quantitative Researcher - Systematic Equities employer: McGregor Boyall
Contact Detail:
McGregor Boyall Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher - Systematic Equities
✨Tip Number 1
Network like a pro! Reach out to professionals in the hedge fund space, especially those who are already working as quantitative researchers. Use platforms like LinkedIn to connect and engage with them; you never know who might have a lead on an opportunity.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your previous work with live equity Alpha signals. This could be through GitHub or a personal website. It’s a great way to demonstrate your expertise and make a lasting impression.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with data exploration, feature engineering, and performance analysis. Practising common interview questions can help you articulate your thought process clearly.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals who can contribute to our systematic equities research function. Your next big opportunity could be just a click away!
We think you need these skills to ace Quantitative Researcher - Systematic Equities
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your strong academic background and any relevant experience in quantitative research. We want to see how your skills in statistics, time-series analysis, and machine learning can contribute to our systematic equities research.
Tailor Your Application: Don’t just send a generic application! Take the time to tailor your CV and cover letter to reflect the specific responsibilities and requirements mentioned in the job description. This shows us you’re genuinely interested in the role.
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 without unnecessary fluff.
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 the process smoother for everyone involved!
How to prepare for a job interview at McGregor Boyall
✨Know Your Numbers
Brush up on your quantitative skills and be ready to discuss specific models or techniques you've used in the past. Make sure you can explain your thought process behind designing and validating Alpha signals, as this will show your depth of understanding.
✨Showcase Your Projects
Prepare to talk about any live signals you've run and the outcomes they produced. Be specific about your role in the research life cycle, from data selection to performance analysis, as this demonstrates your hands-on experience and ownership.
✨Collaborative Mindset
Since the role involves working closely with other researchers, highlight your teamwork skills. Share examples of how you've collaborated on projects, combined signals, or contributed to portfolio discussions to show you're a team player.
✨Stay Current with Trends
Familiarise yourself with the latest trends in systematic equities and machine learning techniques. Being able to discuss recent developments or innovations in the field will impress interviewers and show your passion for research.
