Qualifications

A Ph.D. in Computer Science, Econometrics, Electronic Engineering, Mathematics, Physics or Statistics. You will have a track record of published research work in respected journals. Applications from candidates who have completed a post-doctoral research position are particularly welcome.

 

Relevant Experience

Successful candidates will have substantial academic or trading experience in at least one of the following areas:

• Applied Mathematics such as Cryptography, Fluid Mechanics, and Optimisation.
• Linear and non-linear time series and spectral analysis (ARIMA, TAR, VAR, SSA etc..)
• Machine learning techniques such as DNN's, LSTM, LASSO, Random Forest, and XGBoost.
• Multivariate methods such as PCA and ICA, Factor Analysis, and Cluster Analysis. 

 

Essential Skills:

• Experienced in C++ on very large data sets.
• Self-motivated with high curiosity.
• Ability to work independently and with a team. 

 

Benefits

• Work alongside similar people in an innovative research-driven environment.
• Ability to use new research techniques on ever-growing data sets.
• Highly competitive annual bonus payments to successful candidates who demonstrate positive innovation in models and processes.