An established pod at a $5-20BN hedge fund in London is looking for a quant researcher with demonstrated proficiency in various machine learning techniques to contribute to alpha research and strategy development. This candidate will ideally be looking to develop into a senior quant researcher, managing their own strategies and eventually some risk.
They are running intraday macro strategies, taking a cross-asset approach. The hedge fund have a well-developed infrastructure for systematic trading and provide extensive, high-quality data with the expectation that strategies could quickly go live.
Location: London, Dubai
Key Responsibilities: Research and identify new trading signals and strategies using statistical analysis and machine learning techniques. Develop, test, and implement macro quantitative models aimed at generating alpha across equities, FX, and FI. Collaborate closely with the PM to develop alpha signals and execute in the market. Stay up-to-date with the latest developments in machine learning, quantitative finance, data science, and market trends to drive innovation.
Requirements: Advanced degree (Master's or Ph.D.) in a quantitative discipline such as Mathematics, Machine Learning, Statistics, Physics, Engineering, Computer Science, or a related field. Demonstrated experience in Machine Learning techniques including NLP, Deep Learning, and neural pathways. Strong programming skills in Python, R for algo development and data analysis. Experience statistical modelling and signal generation. Experience working with large datasets, databases, and time series data.
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Key Responsibilities: Research and identify new trading signals and strategies using statistical analysis and machine learning techniques. Develop, test, and implement macro quantitative models aimed at generating alpha across equities, FX, and FI. Collaborate closely with the PM to develop alpha signals and execute in the market. Stay up-to-date with the latest developments in machine learning, quantitative finance, data science, and market trends to drive innovation.
Requirements: Advanced degree (Master's or Ph.D.) in a quantitative discipline such as Mathematics, Machine Learning, Statistics, Physics, Engineering, Computer Science, or a related field. Demonstrated experience in Machine Learning techniques including NLP, Deep Learning, and neural pathways. Strong programming skills in Python, R for algo development and data analysis. Experience statistical modelling and signal generation. Experience working with large datasets, databases, and time series data.
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