Numerical Modelling

Ref.No: NM1113

CommEq develops and implements fully automated behavioural finance trading methodologies.
We identify under-explored data sources and apply advanced proprietary methodologies to generate superior risk-adjusted investment returns.
We’re now scaling up our Research Lab.

You do not need a background in finance to join our team, but you need to be exceptionally talented and hard working. As a member of the team, you will leverage your numerical modelling skills. Working alongside, senior and like-minded colleagues,you will contribute to the enhancement of existing algorithms and innovation of new ones.
This is a strong opportunity for the right individual to work and learn within a cutting edge group. The opportunity potential for career, compensation and skills growth is virtually unlimited.

From a technical perspective you will need to have expertise in numerical modelling and algorithms with manipulating large data sets / measurements. You should be experienced in applying at least one of the following areas of quantitative modelling/numerical algorithms coming out of control theory, operations research (OR), or related:

  • statistics
  • time series analysis
  • stochastic control
  • machine learning
  • dynamic programming
  • digital signal processing / image processing
  • (Markov) discrete state decisions


  • Master or PhD degree in Engineering, Applied Physics, Applied Mathematics or Computer Science.
  • Specialism in researching and developing models and or techniques for mining, analyzing and searching massive data sets or data acquisition & processing.
  • Strong to expert programming skills in a modelling environment such as Python, R, Matlab.
  • Outstanding record of academic and/or professional achievements.
  • Confident and highly motivated personality.

If you think you match the above criteria and want to join an influential team, send your CV and Cover Letter, including the Ref.Number in the subject line.

Only shortlisted candidates will be contacted for an interview.