Our client, a large systematic hedge fund, is keen to hire an experienced Quant Researcher to join their Firmwide Analytics Team in Chicago.
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 will span 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