At a Glance
- Tasks: Research and develop mathematical models for trading opportunities in global markets.
- Company: Join a leading systematic proprietary trading business backed by a top macro hedge fund.
- Benefits: Competitive salary, collaborative environment, and exposure to live trading.
- Other info: High-calibre team with significant ownership and long-term growth potential.
- Why this job: Make a real impact in finance while working with cutting-edge technology and talented professionals.
- Qualifications: PhD in a quantitative field and strong programming skills in Python or C++.
The predicted salary is between 70000 - 90000 £ per year.
Referment are partnering with a highly sophisticated systematic proprietary trading business backed by one of the world’s most respected macro hedge fund platforms. The team is looking to hire exceptional Quantitative Researchers to join a growing research and trading group in London. The role focuses on researching and developing mathematical models used to identify trading and investment opportunities across global financial markets. Researchers work closely with experienced quantitative PMs and engineers in a highly collaborative environment with direct exposure to live trading.
Responsibilities Include:
- Analysing financial and alternative datasets
- Researching and applying machine learning techniques
- Developing quantitative trading signals and models
- Building and maintaining research infrastructure
- Supporting live trading and production systems
Ideal Candidates Will Have:
- A PhD (or equivalent) in Mathematics, Statistics, Physics, Computer Science or a similarly quantitative discipline
- Strong programming skills in Python and/or C++
- Excellent mathematical and statistical foundations
- Exceptional academic backgrounds from leading universities globally
This is an opportunity to join a high-calibre team with significant scope for ownership, impact, and long-term upside.
Quant Researcher (D0BDA4A) in London employer: Referment
Join a leading systematic proprietary trading business in London, where exceptional Quantitative Researchers thrive in a dynamic and collaborative environment. With a strong emphasis on employee growth, you will have the opportunity to work alongside experienced professionals, develop cutting-edge mathematical models, and directly influence live trading strategies. The company fosters a culture of innovation and excellence, providing meaningful challenges and significant long-term career potential.
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We think this is how you could land Quant Researcher (D0BDA4A) in London
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We think you need these skills to ace Quant Researcher (D0BDA4A) in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Referment, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Referment. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Referment
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
