Quantitative Researcher – Systematic Trading | Leading London Hedge Fund

3 days ago


London, United Kingdom Octavius Finance Full time

We are partnering exclusively with a high-profile systematic hedge fund in London to hire a Quantitative Researcher with a strong background in machine learning and systematic trading strategy research.This is a unique opportunity to join a top-tier firm at the forefront of data-driven and algorithmic investing, working alongside exceptional researchers and technologists. The successful candidate will play a key role in designing and implementing next-generation trading models across global equity markets.Key ResponsibilitiesConduct end-to-end quantitative research across large-scale financial, fundamental, and alternative datasets.Design, develop, and implement systematic trading strategies from idea generation through to production.Apply machine learning, statistical modelling, and data science techniques to develop predictive signals and portfolio optimization frameworks.Build and maintain production-quality code for trading and research systems; monitor live predictors and portfolios.Collaborate closely with researchers, engineers, and portfolio managers to refine and scale successful trading ideas.Present research findings clearly and effectively to both technical and investment audiences.Ideal Candidate ProfilePhD (or equivalent research experience) in Mathematics, Statistics, Physics, Computer Science, Engineering, or another quantitative discipline.Demonstrated experience in systematic trading research, with a track record of building mid-to-low frequency equity strategies showing realized Sharpe ratios above Strong proficiency in Python and hands-on experience with data pipeline management, including exploratory data analysis, feature/predictor construction, and performance evaluation.Practical experience using machine learning (supervised, unsupervised, reinforcement learning) and optimisation techniques to automate the search for alpha-generating predictors and portfolios.Exposure to text-based datasets, natural language processing, and embedding-based similarity models is highly desirable.Highly analytical, detail-oriented, and motivated to work in a fast-paced, collaborative, and intellectually rigorous environment.



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