Quantitative Researcher, Systematic Macro
DRW
London
1d ago

DRW is a technology-driven, diversified principal trading firm. We trade our own capital at our own risk, across a broad range of asset classes, instruments and strategies, in financial markets around the world.

As the markets have evolved over the past 25 years, so has DRW maximizing opportunities to include real estate, cryptoassets and venture capital.

With over 1000 employees at our Chicago headquarters and offices around the world, we work together to solve complex problems, challenge consensus and deliver meaningful results.

It’s a place of high expectations, deep curiosity and thoughtful collaboration.

As a Quantitative Researcher , you will join a small trading team with a systematic macro mandate. You will be tasked with solving challenging problems arising in a trading environment while utilizing statistical and machine learning techniques as the group continues to research and deploy new strategies.

You will join a team with a start-up feel, and work directly with experienced traders and machine learning experts that are intellectually curious across the spectrum of finance, mathematics, and technology.

How you will make an impact :

  • Formulate and apply mathematical modeling and quantitative techniques such as machine learning or econometrics to systematically identify and monetize trading opportunities across currencies, commodities and fixed income products.
  • Work closely with traders and researchers to build, automate and improve existing trading and monitoring tools, strategies and research infrastructure
  • Keep abreast of the latest academic and market research in order to advance the groups research agenda.
  • What you bring to the team :

  • 2-3 years of professional experience as a Quantitative Researcher conducting systematic alpha research, portfolio optimization, etc.
  • Have completed a degree in a technical discipline with a focus on statistics, econometrics, mathematics, computer science or related fields.
  • Proficiency in Python programming experience using the machine learning stack : numpy, pandas, scikit-learn, pytorch, etc.
  • Strong analytical and problem-solving skills including a solid foundation of statistics knowledge
  • Solid mathematical and analytical ability; exceptional problem-solving and modeling ability
  • Self-motivated and able to work collaboratively and productively with others. Strong sense of accountability and desire to continuously learn
  • Excellent written and verbal communication skills to report research results as well as methodologies
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