Machine Learning Quant Researcher
Why This Role Stands Out
This on-site Machine Learning Quant Researcher role offers a highly competitive salary of £150,000-£200,000, plus a discretionary bonus, for individuals passionate about applying cutting-edge ML techniques to financial markets. You'll thrive here if you possess a strong quantitative background and enjoy collaborating with a global team to develop innovative trading strategies, driving significant impact within a respected firm. Apply now to advance your career in systematic trading and machine learning research.
Quick Overview
Job Description
Discretionary end of year bonus
Onsite WORKING
Location: Central London, Greater London - United Kingdom Type: Permanent
Machine Learning/Data Science Quantitative Researcher - London/Paris
My client is a quantitative hedge fund with offices globally, focusing on systematic trading. Their Quant Researchers develop and monitor strategies covering all liquid markets, including HFT/arbitrage, statistical arbitrage, CTA, Macro and event-driven models. The firm has a mandate for Quantitative Researchers who are specialised in Machine Learning, Deep Learning, Reinforcement Learning, NLP, or Computer Vision. Successful applicants will apply these techniques to analyse datasets and identify trading opportunities, and develop them into monetizable strategies in collaboration with other researchers, developers, and traders.
The Role:
- Researching and applying Machine Learning and other Data Science techniques to analyse datasets and identify alphas.
- You will work closely with other researchers, developers and traders on the development and implementation of these strategies, and monitor their performance over time.
- Quantitative Researchers collaborate with each other globally. You will share ideas and work on tools for others to use across the firm, expanding the business and building your own skills.
- An academic background with degrees covering numerical fields of study, such as Computer Science, Mathematics, and Quantitative Finance, PhD level degrees are preferred but not required.
- Experience/knowledge of finance from academic studies, internships or professional experience.
- Coding proficiency in at least on language, successful candidates are typically expert users of Python, and proficient with data science libraries.
Skills
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