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Machine Learning Quant Researcher

eFinancialCareers·London (South East England)On-site
£150 000 – £200 000 / yearestimated
Vox Summary
  • Role Focus: Researching and applying Machine Learning and Data Science techniques to analyze datasets and identify alphas for trading strategies.
  • Collaboration: Work closely with researchers, developers, and traders to develop, implement, and monitor quantitative strategies across liquid markets.
  • Requirements: Academic background in numerical fields; experience or knowledge of finance; coding proficiency, especially in Python with data science libraries.
  • Conditions & Benefits: Onsite working in Central London; salary range of £150,000-200,000 GBP; discretionary end-of-year bonus; permanent position.
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Job description

£150,000-200,000 GBP 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. Requirements: • 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.

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Original source
reed.co.uk
Posted
Jul 13, 2026 · true date
Last verified
1 hour ago
Quality score
35/100
Salary stated0
Company identified0
applyUrl0
postedAt15
Complete description20

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