Systems Architect (KTP Associate) (1342) - Kingston University London

This is an exciting and challenging opportunity for an ambitious graduate, supported by Kingston University academics and based at Instinet, a leading global broker of equities, in London. This KTP project will develop and deploy innovative machine learning techniques for trading execution performance and monitoring. You will lead the development of theoretical, practical and organizational capabilities, to deploy machine-learned products to improve the execution performance of equity trading, and machine-learned tools to monitor this performance. You will also have responsibility for authoring reports and academic publications that describe aspects of your work, and the potential impact for Instinet and its clients. You will be working alongside another KTP Associate, employed as a Machine Learning Scientist.