Quantitative systematic investment manager trading across all asset classes
QRT is a London-based systematic investment manager whose stack pairs Python, Polars and C++ research tooling with a heavy data layer of Kafka (AWS MSK), Spark, Trino, ClickHouse and CockroachDB on Kubernetes. Hiring is accelerating and skews toward engineering and data, matching active builds of a next-generation research platform, high-performance research storage and a risk data platform, alongside recurring pain around pipeline latency and dataset reliability.
Qube Research & Technologies is a quantitative investment manager founded in 2018 and headquartered in London, running systematic strategies across every major asset class. The firm employs between 1,001 and 5,000 people across 16 offices worldwide, managing capital on behalf of investors. Its operations combine research, data engineering, technology and trading functions. Current hiring spans France, the United Kingdom, China, Australia, the Netherlands, Switzerland and India. The firm also backs coding initiatives and academic programs promoting maths and science education.
QRT uses Python, C++, Pandas, Polars and NumPy for research, with Kafka, Spark, Airflow, Trino, ClickHouse and CockroachDB for data, running on AWS (EKS, EMR, MSK, RDS) via Kubernetes, Terraform and Helm.
QRT is hiring in France, the United Kingdom, China, Australia, the Netherlands, Switzerland and India, with engineering and data roles leading the mix.
Active projects include a next-generation research platform, high-performance storage for research workloads, a next-generation trading analytics platform, a risk data platform and on-premise trading hardware.
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Qube Research & Technologies's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.