A fundamental change in finance in the last few decades is the on-going exponential growth in the amount of available data. Our researchers develop investment ideas by finding patterns in large, noisy and rapidly changing real-world data sets, trying to extract underlying causes and effects. They apply scientific methods from diverse disciplines including Bayesian statistics, signal processing and machine learning. The role involves seeking these signals using techniques such as time series analysis, probability theory and regression analysis.
For the internship you will be paired with a member of the Quant team as a mentor and work on a research project that is business critical. The role will reflect the potential of a full time position in the company. We aim to make the project interesting and similar to the work that an entry level Quant might first embark on. The salary is competitive and the working hours 9-6pm.