Trexquant is a systematic hedge fund where we use thousands of statistical algorithms to trade equity and futures markets globally. Starting with many data sets, we develop a large set of features and use various machine learning methods to discover trading signals and effectively combine them into market-neutral portfolios. We are looking for scientists, engineers, economists, and programmers to develop the next generation of machine learning strategies that can accurately predict the future movements of liquid financial assets.

Responsibilities

• Design, implement, and optimize various machine learning models aimed at predicting liquid assets using a wide set of financial data and a vast library of trading signals
• Parse data sets to be used for alpha (strategy) development
• Investigate and implement state-of-the-art academic research in the field of quantitative finance
• Collaborate with experienced and resourceful q...