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- Tasks: Join a dynamic team to develop and refine systematic equity strategies that drive investment success.
- Company: A small, entrepreneurial investment team in Zug, Switzerland, focused on collaboration and innovation.
- Benefits: Exceptional career growth opportunities in a fast-paced, intellectually stimulating environment.
- Why this job: Make a real impact on portfolio construction and alpha generation with your research.
- Qualifications: Strong programming skills in Python and a degree in a quantitative field.
- Other info: Ideal for those who thrive in autonomy and enjoy working in a lean team structure.
The predicted salary is between 36000 - 60000 £ per year.
We are recruiting on behalf of a small, highly collaborative, and entrepreneurial systematic investment team seeking a talented Quantitative Researcher to help expand their global systematic equities strategies. This is an outstanding opportunity to join a high-performing group where your research will have direct impact on portfolio construction and alpha generation. The environment is fast-paced, intellectually rigorous, and offers exceptional long-term career growth.
Role Overview
As a Quantitative Researcher, you will work closely with the Senior Portfolio Manager and other researchers to develop, test, and refine systematic equity signals and strategies. You will contribute across the full research lifecycle from idea generation and dataset exploration to modelling, backtesting, and deployment. This role is ideal for someone who thrives in a lean team structure, enjoys autonomy, and brings both strong technical skills and economic intuition.
Key Responsibilities
- Collaborate directly with the Senior Portfolio Manager on alpha research, including signal discovery, hypothesis testing, and performance evaluation.
- Conduct research using diverse financial and alternative datasets, applying statistical techniques to uncover predictive relationships.
- Develop and backtest systematic equity strategies, ensuring robustness across regions, regimes, and market conditions.
- Explore and implement machine learning or NLP-based approaches depending on your academic and research background.
- Combine strong financial intuition with statistical learning to build predictive models that directly impact trading decisions.
- Contribute to the improvement of the team's research tools, workflows, and data-processing pipelines.
Preferred Technical Skills
- Strong programming and research skills, especially in Python.
- Solid understanding of statistical modelling, predictive modelling, and data analysis.
- Degree from a top-tier university in a quantitative field such as Data Science, Computer Science, Statistics, Applied Mathematics, Physics, or Engineering.
- Background in machine learning is particularly welcome.
Preferred Experience
- 3 years of experience within a systematic trading environment, ideally focused on equities.
- Hands-on experience with statistical modelling and signal research for equity markets.
- Prior research applying machine learning techniques to return prediction is a strong plus.
Highly Valued Attributes
- Experience within buy-side quantitative trading teams.
- Strong economic intuition alongside analytical depth.
- Creativity, critical thinking, and a genuine passion for exploratory research.
- Experience working with equity datasets and understanding market microstructure.
- Ability to work independently in a fast-moving research environment while still thriving in a collaborative team structure.
Quantitative Researcher Systematic Equities - Zug, Switzerland in London employer: Marlin Selection
Contact Detail:
Marlin Selection Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher Systematic Equities - Zug, Switzerland in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the systematic equities space on LinkedIn or at industry events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your quantitative research projects, especially those involving Python and machine learning. This will give potential employers a taste of what you can bring to their team.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and market trends. Be ready to discuss your past research and how it relates to their strategies. Confidence and clarity are key!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who take the initiative. Plus, it shows you're genuinely interested in joining our collaborative team.
We think you need these skills to ace Quantitative Researcher Systematic Equities - Zug, Switzerland in London
Some tips for your application 🫡
Show Your Passion for Research: When writing your application, let your enthusiasm for quantitative research shine through. Share specific examples of projects or experiences that sparked your interest in systematic equities and how they relate to the role.
Highlight Your Technical Skills: Make sure to emphasise your programming prowess, especially in Python, and any experience with statistical modelling or machine learning. We want to see how your skills can contribute to our team's success in developing robust equity strategies.
Tailor Your Application: Don’t just send a generic application! Tailor your CV and cover letter to reflect the key responsibilities and preferred skills mentioned in the job description. Show us how your background aligns with what we’re looking for.
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 about the process!
How to prepare for a job interview at Marlin Selection
✨Know Your Numbers
Brush up on your quantitative skills and be ready to discuss specific statistical models or techniques you've used in the past. Be prepared to explain how these methods can apply to systematic equities, as this will show your technical prowess and understanding of the role.
✨Showcase Your Research
Bring examples of your previous research projects, especially those involving signal discovery or machine learning. Discuss the challenges you faced and how you overcame them, as this demonstrates your problem-solving abilities and creativity in a fast-paced environment.
✨Understand the Market
Familiarise yourself with current trends in the equity markets and be ready to discuss how they might impact systematic strategies. This shows that you have a strong economic intuition and are genuinely interested in the field, which is crucial for a Quantitative Researcher.
✨Collaborative Mindset
Emphasise your ability to work within a team while also thriving independently. Share examples of how you've collaborated with others in past roles, particularly in a research setting, to highlight your fit for their highly collaborative and entrepreneurial team culture.