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Trexquant is a systematic hedge fund where we use thousands of statistical algorithms to trade equity markets all over the world. We develop and use machine learning methods to discover trading signals and effectively combine them into market-neutral portfolios. Our firm has grown significantly in recent years. We have increased the breadth of markets in which we participate, the number and scale of our data sources, as well as the complexity of our forecasting algorithms.

 As a member of the Strategy team at Trexquant, you will be developing systematic strategies based on a variety of machine learning and statistical methods. The data you train and validate comes from actual market trading. If you are interested in working with the latest machine learning techniques at a growing systematic hedge fund, we invite you to apply for the Strategy Researcher position at the link provided here.


  • Development, implementation, and optimization of machine learning models aimed at predicting equity market dynamics using a wide set of financial data and a vast library of trading signals
  • Use your methods to create systematic trading strategies and run fund capital in global markets
  • Investigate and implement recent academic research
  • Collaborate with experienced quantitative researchers and other Strategy Researchers

Desired qualifications:

  • A post-graduate degree in a technical discipline (mathematics / physics / finance / others)
  • Programming experience (Python, C/C++, other languages)
  • Knowledge of probability theory, machine learning, and optimization concepts
  • Ability to work independently and take projects to completion, ability to quickly learn about new systems, ability to communicate complex concepts, creative thinking, and attention to details


  • Competitive salary plus bonus tied to the performance of strategies you develop
  • Comprehensive benefits including healthcare and insurance