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Quantitative Researcher - Equities

London, United Kingdom

IMC is looking for experienced quantitative researchers to develop high to mid frequency delta one trading strategies and predictive models for Equities markets. If you’re excited about helping to push the boundaries of what we can do with Machine Learning in trading, unlocking the significant edges we have in execution, and collaborating to become the best trading firm worldwide, this may be the role for you.

We have longstanding and significant edges across market access, global reach, Options understanding and low latency. The rapid growth we’ve already seen in Machine Learning has unlocked these edges, and some of the most interesting and impactful problems are now being tackled.

IMC competes and wins as a team, with open idea sharing and collaboration across disciplines, desks and offices.

Your Core Responsibilities:

  • Conduct large-scale data analysis to generate statistically robust predictions of market behavior, which guide all trading decisions and drive high-impact improvements across global offices.
  • Work as part of an established and expanding research team, collaborating closely with traders, software and hardware developers globally to enhance our models and drive measurable improvements in production performance.
  • Contribute to defining the strategic direction of research and tooling initiatives.
  • Leverage creativity and expertise to quickly produce high-quality, testable ideas.
  • Apply a disciplined and systematic approach to ensure results are robust and thoroughly validated.
  • Build a deep understanding of market dynamics and potential optimization areas, working closely with operational traders to implement improvements.

Your Skills and Experience:

  • Graduate & Postgraduate studies from a leading University; majoring in Machine Learning, Statistics, or STEM related subjects.
  • 3+ years’ experience as a Quantitative Researcher, with specific experience in the high to mid-frequency delta one space, ideally within Equities markets.
  • A proven track record of developing value-adding and orthogonal features across multiple families.
  • Practical experience extracting value from a range of sources (both public feed and alternative data).
  • Strong programming skills in at least one language (python preferred).
  • Solid understanding of statistics.
  • Significant practical experience with at least one mainstream ML approach is required, whilst familiarity with a variety of machine learning approaches and the risks of overfitting is preferred.
  • Exceptional interpersonal and communication skills, combined with a proven capacity to collaborate across disciplines and work autonomously to achieve goals.

About Us

IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we’ve been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.

 

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IMC Voluntary Disclosure

At IMC, we understand the importance of diversity, equity and inclusion, and are committed to continually improving this in our recruitment process. As part of our commitment, we have added an additional question below, to better understand our candidates, and focus our marketing, sourcing and interviewing efforts, to ensure equitable outcomes. This question is voluntary, and the information you provide will only be used for the purpose stated above and will not be shared with interviewers in the application process. If you do not wish to provide a response to the question, there will be no adverse impact on your application.

 

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