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- Tasks: Design and improve algorithmic trading strategies using Python and statistical models.
- Company: Join a dynamic team focused on innovative trading solutions in CeFi and DeFi markets.
- Benefits: Enjoy a hybrid work model, competitive pay, and performance-based bonuses.
- Why this job: Make a real impact in a fast-paced environment with autonomy and collaboration.
- Qualifications: Strong Python skills and a background in quantitative fields like Math or Physics required.
- Other info: Ideal for those with experience in trading signal research or competition wins.
The predicted salary is between 43200 - 72000 £ per year.
We’re hiring a Quantitative Researcher with strong Python skills and a solid foundation in statistics and probability theory. This role involves designing and improving algorithmic trading strategies across CeFi and DeFi markets, including spot, derivatives, and ETPs. You’ll work closely with researchers, traders, and developers to build and optimize models, using large-scale market data and simulation tools. Depending on your experience, you will either focus on market making and high-frequency signals or machine learning-driven signal research and automation.
What we are looking for:
- Strong coding ability in Python (C++ is a plus)
- Background in a quantitative field (Math, Physics, CS, etc.)
- Experience with statistical modeling and/or ML techniques
- Track record in trading signal research, strategy design, or competition wins (e.g. Kaggle, Olympiads)
Nice to have:
- Experience in HFT/MFT strategy development
- Familiarity with trading infrastructure and market microstructure
What is on offer:
- High-impact work with autonomy from day one
- Fast-paced, flat-structured environment without bureaucracy
- Competitive compensation, including performance-based upside
Quantitative Researcher (London Area) employer: Durlston Partners
Contact Detail:
Durlston Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quantitative Researcher (London Area)
✨Tip Number 1
Network with professionals in the quantitative finance space. Attend meetups, webinars, or conferences related to algorithmic trading and quantitative research. Engaging with industry experts can provide insights into the role and may even lead to referrals.
✨Tip Number 2
Showcase your Python skills through personal projects or contributions to open-source repositories. Having a portfolio that demonstrates your coding ability and understanding of statistical models will make you stand out to us.
✨Tip Number 3
Participate in online competitions like Kaggle or similar platforms. This not only sharpens your skills but also provides tangible evidence of your capabilities in trading signal research and strategy design, which is highly relevant for this role.
✨Tip Number 4
Familiarise yourself with market microstructure and trading infrastructure. Understanding how markets operate at a granular level can give you an edge in discussions during interviews and demonstrate your commitment to the field.
We think you need these skills to ace Quantitative Researcher (London Area)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your strong Python skills and any relevant experience in quantitative fields like Math, Physics, or Computer Science. Include specific projects or competitions that showcase your coding ability and statistical modelling expertise.
Craft a Compelling Cover Letter: In your cover letter, express your passion for algorithmic trading and how your background aligns with the role. Mention any experience you have with trading signal research or strategy design, and be sure to highlight your familiarity with both CeFi and DeFi markets.
Showcase Relevant Projects: If you've worked on any projects related to high-frequency trading, machine learning, or statistical modelling, include these in your application. Provide links to your GitHub or any relevant portfolios to demonstrate your practical skills.
Prepare for Technical Questions: Anticipate technical questions related to Python coding, statistics, and probability theory during the interview process. Brush up on your knowledge of market microstructure and trading infrastructure to impress your interviewers.
How to prepare for a job interview at Durlston Partners
✨Showcase Your Python Skills
Make sure to highlight your proficiency in Python during the interview. Be prepared to discuss specific projects where you've used Python for quantitative analysis or algorithmic trading, and consider bringing along code samples to demonstrate your coding ability.
✨Demonstrate Your Statistical Knowledge
Since a solid foundation in statistics and probability theory is crucial for this role, be ready to explain key concepts and how you've applied them in past projects. You might also want to prepare for questions that test your understanding of statistical modelling and machine learning techniques.
✨Discuss Your Trading Experience
If you have a track record in trading signal research or strategy design, make sure to share specific examples. Discuss any competitions you've participated in, like Kaggle or Olympiads, and how those experiences have shaped your approach to quantitative research.
✨Familiarise Yourself with Market Microstructure
Understanding trading infrastructure and market microstructure can set you apart from other candidates. Brush up on these topics and be ready to discuss how they relate to high-frequency trading (HFT) and market making strategies, as this knowledge could be beneficial in your role.
