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The role will involve designing and developing real-time analytics models; enhancing research framework; improving machine learning, data mining and web scraping capabilities; and acquiring, cleaning and processing large amounts of structured and unstructured data. The position spans firmwide activities, and will afford exposure to all of the products and strategies the firm trades, as well as the various quant and trading heads across the business.
Designing and developing real-time analytics models
Improving capabilities in relation to machine learning, data mining and web scraping
Analysing large, disparate sets of structured and unstructured internal and market data
Contributing with strategic direction, helping to optimise the performance of the team
5+ years' experience in a Quant Research / Data Science role at a financial institution
PhD from a top university in a highly quantitative subject (e.g. Applied Mathematics, Physics, etc.). Additional studies in Finance, Economics, etc. would be advantageous
Proficiency with Kdb+/q, Python, C++ and SQL, and experience building machine learning algorithms (e.g. decision tree, random forest, etc.)
A working knowledge of the financial markets and post-trade analysis