Quant Engineer (various seniority levels)

  • Anywhere

swissQuant Group provides quantitative services, consultancy and products for financial and industrial clients, including a number of global Fortune 500 companies. Our business edge originates from the effective translation of Intelligent Technology into measurable, bottom-line client value. swissQuant Group is a privately held company incorporated in 2005 as a spin-off of ETH Zürich.

SwissQuant – London
Due to our rapid growth over the past years, swissQuant Group is expanding its geographic footprint globally. Our expansion in London is a key cornerstone for this strategic priority. This offers a unique combination of opportunities in our London office for personal development, as well as varied challenges to push your boundaries.

This opening is for a quantitative role with responsibility for researching, developing and maintaining quantitative models and associated IT infrastructure. Topics will vary greatly depending on live projects but will mainly revolve around topics in quantitative finance and/or statistical learning (machine learning).

  • Accountabilities
    Design, build and deliver robust and production quality models and code within a unified library.
  • Assist with the systematic review and on-going assessment of existing models.
  • Liaise with senior stakeholders to ensure that the model meets their requirements and ensure that they agree with the modelling assumptions and understand the associated risks.
  • Deliver high quality documentation and presentations to support and maintain model and library use.
  • You will work on the development of cutting-edge methodologies and technologies for major international clients.

Your tasks will include designing, prototyping and testing quantitative models applied to finance in a real-world context. It may also include presenting your work and ideas to people with a diverse spectrum of experience and domain knowledge. You will also engage and participate in all phases of transformation of a quantitative idea into a final product or service, from the Proof-of-Concept to client deliverables.

Work is done both in a client project context as well as internal innovation / research tasks. This requires a high level of hard and soft skills which you will contribute as a team member. Your personal success will depend equally on your ability to conceptualize and develop state-of- the-art models as well as your ability to function well within a team.

  • Stakeholder Management / Leadership
  • Facilitate and challenge discussion of modelling options with senior stakeholders.
  • Facilitate the gathering and documentation of model requirements.
  • Facilitate the gathering and documentation of model requirements.
  • Communication and explanation of model results to stakeholders.
  • Decision-making and Problem Solving
  • Ability to convert business objectives into technical modelling solutions.
  • Ability to convert business objectives into technical modelling solutions.
  • Risk and Control Objective
  • Ensure that all activities and duties are carried out in full compliance with regulatory requirements, enterprise wide risk mitigation guidance and internal swissQuant policies and standards.


  • Post graduate degree in a highly quantitative discipline.
  • Fluency in English, German is a plus.
  • Eligibility to work in the UK.
  • Strong industry experience in a highly quantitative role. This may be substituted by relevant academic experience in a quantitative discipline.
  • Able to deliver to tight deadlines on quantitative projects.
  • Able to work in a highly dynamic environment.
  • Python (preferred), R or MATLAB advanced proficiency (C++ or Java is a plus).
  • Good understanding of statistical and econometric modelling techniques – e.g. time series
  • Analysis, regression models and various estimation techniques, machine learning


  • PhD in a highly quantitative discipline.
  • Experience in designing and developing statistical and econometric and machine learning models.
  • Experience in analysing large volumes of data including cleaning and subsequent pattern identification and clustering.
  • Knowledge of financial markets and products.