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Oxford Knight is seeking a Python-focused Quantitative Researcher for a London-based latency team. You will analyze billions of trading data points and collaborate with trading teams to uncover actionable insights that drive infra and strategy.
Ideal candidates have 2+ years in quantitative research, strong Python, ML, statistics, and optional C++/SQL experience; you’ll design data mining and machine learning solutions to create competitive edges in a high-performance environment.
Leading HFT fund looking for a self-driven quantitative researcher to join their centralised Latency team where you will draw on your problem-solving skills and data science/statistics experience to analyse billions of collected trading data points and unearth competitive edges.
This role offers the opportunity to develop both business and technical expertise; working closely with trading teams to perform post-trade statistical analysis and identify relationships between business metrics and changes on the infrastructure technology. You’ll also investigate and design data mining and machine learning algorithms.
Unique in their field, this global firm combines the lively, positive spirit of a start-up with the stability of a longer-established player. This role would suit a curious, highly collaborative researcher who has demonstrated the ability to independently drive projects to completion.
Requirements
NB: Please do not apply if you’re a fresh graduate.
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Python Quantitative Researcher – London London