Marshall Wace

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Quantitative Researcher - Volatility Strategies (London)

Founded in 1997, Marshall Wace is one of Europe's leading Hedge Fund Managers with approximately $39 billion assets under management. It enjoys a strong reputation in the industry for its success, influence and innovation, built by a dedicated team of people working in a dynamic, entrepreneurial culture. Our firm is made up of over 250 professionals operating from established offices in London, New York and Hong Kong.

Full Description

Quantitative Research – Systematic Volatility


The Systematic Volatility team is responsible for the creation and management of fully automated systematic investment strategies that focus on the volatility asset class. The team operates at the intersection of quantitative modelling, technology and portfolio management and is therefore highly interdisciplinary. As a quantitative analyst, you will have exposure to the full systematic investment process across idea generation, volatility modelling, portfolio construction, execution, post-trade reconciliation, risk and portfolio management. This is a hands-on role responsible for creating and optimising new quantitative systematic portfolio models.


Core responsibilities will include:

  • Research and implement key methods and technologies to facilitate the quantitative investment process of volatility products
  • Analyse large data sets, automate the extraction of key features, modelling of information for investment, execution, risk and portfolio management purposes
  • Develop strong understanding of the volatility market, including the various products, exposures, behaviours and execution across all exchanges globally and OTC markets


Successful candidates are likely to have a combination of the following key skills:

  • PhD or Masters degree in a quantitative discipline
  • At least three years buy side or sell side experience modelling, pricing and / or developing investment strategies that trade options and other volatility derivatives
  • Strong coding expertise in either Matlab, Python, R, Java, C# or C++
  • Experience of working with large & complex data sets
  • Time series modelling / simulation or quantitative research experience
  • A solid foundation in optimisation, probability and statistics
  • Practical approach to problem solving
  • Outstanding quantitative, analytical and problem solving skills
  • Good communication skills
  • Detail oriented