Machine learning Researcher

London, UK
24 Apr 2019
26 Apr 2019
Job role
About Arabesque

Arabesque is a global investment management and technology firm that brings a new dimension to investing, using self-learning quant models and big data to assess the performance and sustainability of globally listed companies. Arabesque offers investment solutions to clients in addition to being a provider of sustainability data originating from our proprietary technology Arabesque SRay ®.

Arabesque S-Ray® is a technology firm that combines big data and machine learning to provide data services to empower investors, corporates and other stakeholders to make more sustainable decisions.

Our story is one of partnership between leaders in finance, mathematics, and sustainability working together to accelerate the transition to a more sustainable future. With a mission to make sustainable and responsible investing available to all, and to empower people through data, we believe that finance can be a catalyst of change.

With headquarters in London and offices in Frankfurt, Singapore, and Boston, the firm is in a period of rapid international growth.


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.

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