Quantitative Researcher

DRW is a diversified, technology-led principal trading firm. We trade our own capital at our own risk, across a broad range of asset classes, instruments and strategies, in markets around the world. As the markets have evolved over the past 25 years, so has DRW – growing to include real estate, cryptocurrencies, venture capital and several industry acquisitions. With more than 800 employees at our Chicago headquarters and six global offices, we work together to solve interesting problems and capture opportunities. It’s a place of high expectations, deep curiosity, and constant collaboration, with some of the smartest, most passionate people you’ll meet. 

Our Quantitative Research team is looking for a passionate and innovative Quantitative Researcher to use existing DRW resources and data to improve EDT strategies and research new trading ideas. Working at the cutting edge of the interface between trading and technology for one of the world's leading trading firms. This role is a rare opportunity to jump straight into a trading role - your successful ideas will become part of our array of quantitative strategies, allowing you to have an impact on our bottom line right away.

 

What you will be working on:

  • Carrying out data analysis and mathematical modelling on large sets of time-series data
  • Designing, developing and optimizing profitable proprietary trading algorithms

 

Qualifications:

  • Master’s degree, ie a post graduate research-based qualification in a quantitative subject such as; Computer Science, Physics, Engineering, Math - from a top tier university
  • Good basic applied statistics skills
  • Innovative thinker, with excellent design, debugging and problem-solving skills
  • Strong Python programming skills and experience of Linux OS
  • Good communication and documentation skills
  • Team player who is motivated to learn about trading and financial markets
  • Happy in fast paced environment where there is pressure to deliver results

Nice to have:

  • Excellent and proven applied statistics skills
  • Have proven experience of successfully using quantitative analysis and programming skills to solve complex problems
  • Capable of independent research - demonstrated by evidence of a successful research project 
  • Excellent understanding of machine learning techniques
  • Proven practical experience with predictive modelling
  • Skilled in advanced data visualization

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