The AI team primarily works on Arabesque’s AI engine which delivers investment recommendations for the purposes of fund management. We have over 50 R&D projects in the pipeline with an ultimate goal of building a 'general AI' engine within the financial space. Our work covers a broad spectrum of science-based fields deploying approaches from Supervised and Unsupervised Learning, Feature Engineering, Natural Language Processing, Ensemble Methods, Network Analysis, Bayesian Approaches, Signal Processing, Portfolio Optimisation, Agent Based Modelling and Swarm Intelligence. We are looking for candidates with research experience in one or more of these fields.
We are also interested in high performance and distributed computing candidates. Candidates would ideally be familiar with one or more of the following tech stacks: Apache Cassandra, Kafka, Spark, Kubernetes, Cloud Computing (AWS, Google, Azure). We also employ various object store and database systems. Experience with computational graphs is a plus.
While candidates are not required to have a knowledge of finance and professional experience is not a necessity, candidates would have ideally engaged in personal side projects or the open source community.
We generally prefer to fill PhD level 3-6 month internship roles but will consider MSc students and full-time roles. They salary package for full time roles is competitive. The closing date for applications is November 2019.