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- Tasks: Join us as a Quantitative Researcher to build and optimise trading models.
- Company: We are a leading firm in systematic trading based in London.
- Benefits: Enjoy competitive compensation with performance-based bonuses and hybrid work options.
- Why this job: Dive into a dynamic environment, collaborating with experts and making an impact in trading.
- Qualifications: Strong Python skills and a background in Math, Physics, or Computer Science required.
- Other info: Experience with statistical modelling or machine learning techniques is a plus.
The predicted salary is between 36000 - 60000 £ per year.
We’re hiring a Quantitative Researcher with strong Python skills and a solid foundation in statistics and probability theory. 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.
- 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
Competitive compensation, including performance-based upside.
Researcher (f/m/d) employer: Durlston Partners
Contact Detail:
Durlston Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Researcher (f/m/d)
✨Tip Number 1
Brush up on your Python skills! Since strong coding ability in Python is a must for this role, consider working on personal projects or contributing to open-source projects that involve quantitative analysis or trading algorithms.
✨Tip Number 2
Familiarise yourself with statistical modelling and machine learning techniques. You could take online courses or read relevant literature to deepen your understanding, which will help you stand out during discussions with our team.
✨Tip Number 3
Network with professionals in the quantitative finance field. Attend meetups, webinars, or conferences where you can connect with researchers and traders, as these connections might provide valuable insights and even referrals.
✨Tip Number 4
Prepare to discuss your experience with large-scale market data and simulation tools. Think of specific examples from your past work or studies that demonstrate your ability to handle complex datasets and derive actionable insights.
We think you need these skills to ace Researcher (f/m/d)
Some tips for your application 🫡
Highlight Relevant Skills: Make sure to emphasise your strong Python skills and any experience you have with C++. Mention your background in quantitative fields like Mathematics, Physics, or Computer Science, as well as your familiarity with statistical modelling and machine learning techniques.
Showcase Your Experience: Detail any previous roles or projects where you've worked with large-scale market data or simulation tools. If you've focused on market making, high-frequency signals, or machine learning-driven signal research, be sure to include specific examples.
Tailor Your CV: Customise your CV to align with the job description. Use keywords from the job posting, such as 'quantitative researcher', 'statistical modelling', and 'automation', to ensure your application stands out to recruiters.
Craft a Compelling Cover Letter: Write a cover letter that not only outlines your qualifications but also expresses your enthusiasm for the role. Discuss why you're interested in working with this company and how your skills can contribute to their success in systematic trading.
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 research, and consider bringing examples of your code or models to demonstrate your skills.
✨Understand Statistical Concepts
Brush up on your knowledge of statistics and probability theory. Be ready to explain key concepts and how they apply to quantitative research, as well as any relevant experience you have with statistical modelling or machine learning techniques.
✨Familiarise Yourself with Market Data
Since the role involves working with large-scale market data, it’s essential to understand how to analyse and interpret this data. Prepare to discuss any experience you have with market data analysis and how you’ve used it in previous roles.
✨Prepare for Technical Questions
Expect technical questions related to both coding and quantitative methods. Practice solving problems on the spot, as interviewers may ask you to write code or solve a statistical problem during the interview to assess your thought process and problem-solving abilities.
