At a Glance
- Tasks: Analyse market data and develop AI-driven trading strategies.
- Company: Dynamic firm in Central London focused on research and collaboration.
- Benefits: Competitive salary, career progression, and a collaborative culture.
- Other info: Opportunity to work with diverse asset classes and innovative strategies.
- Why this job: Join a cutting-edge team and make an impact in AI/ML finance.
- Qualifications: Bachelor’s degree and strong Python skills required.
The predicted salary is between 50000 - 120000 £ per year.
We are seeking a Quantitative Researcher specializing in AI and Machine Learning to join a dynamic team in Central London. This role is permanent and offers a competitive salary ranging from £50,000 to £120,000 GBP, depending on experience.
The organization values research and collaboration, creating an environment where researchers and portfolio managers work closely together. Initially focused on cash equities, the firm has expanded its operations globally, employing a diverse range of strategies across various asset classes. The team is particularly interested in candidates with experience in AI and ML from hedge funds or tech firms who are eager to engage more deeply with research.
Key Responsibilities- Utilize datasets to identify trends and patterns in the markets.
- Apply data-driven techniques, including feature engineering, predictive modeling, and machine learning algorithms, to enhance signal generation and improve strategy robustness.
- Translate successful research into production-ready systematic trading strategies, monitoring performance and analyzing results.
- Continuously refine models using new data and insights.
- Contribute to portfolio optimization by developing advanced models, analytical tools, and AI-driven frameworks to assess risk, performance attribution, and portfolio behavior.
- Assist in building scalable research infrastructure and quantitative solutions that enable informed, data-driven investment decisions.
- Strong hands-on experience using Python.
- Experience with C++ or Java is a plus.
- Previous successful candidates have worked at top franchises in leading investment banks or hedge funds.
- Experience in pricing or modeling is preferable.
- Experience in alpha research and signal/strategy development is advantageous.
- A completed or in-progress Master’s Degree in a quantitative discipline such as Mathematics, Computer Science, Statistics, Physics, or Electrical Engineering.
- Competitive compensation package.
- Flat meritocratic structure and collaborative culture.
- Opportunity to invest in the internal fund.
- Excellent scope for career progression within the firm.
- Exposure to various types of strategies and asset classes.
This role offers a unique opportunity to work at the intersection of quantitative research and AI/ML, contributing to innovative trading strategies in a supportive and growth-oriented environment.
Quantitative Researcher – AI/ML in London employer: Anson McCade Recruitment
Anson McCade Recruitment is an exceptional employer, offering a vibrant work culture in Central London that fosters collaboration and innovation. With a flat meritocratic structure, employees benefit from competitive compensation, opportunities for career progression, and the chance to engage with cutting-edge AI and ML technologies in quantitative research. The firm prioritises employee growth and provides exposure to diverse strategies across global markets, making it an ideal place for those seeking meaningful and rewarding careers.
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We think you need these skills to ace Quantitative Researcher – AI/ML 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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✨Brush Up on Your Statistics
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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.
