Trade surveillance and market abuse detection software for financial firms
TradingHub builds trade surveillance software that models market risk and trader intent to flag abuse across instruments for banks, funds and brokers. Its stack pairs Python, C++ and C# with PyTorch, TensorFlow, scikit-learn and AWS Bedrock, signaling quant-heavy detection logic. Hiring splits evenly between engineering and support, with recurring cloud-cost and lean-team pressures pointing to a services-intensive deployment model.
TradingHub is a privately held company founded in 2010 and headquartered in London, England, with 51–200 employees. It sells trade surveillance software to investment banks, asset managers, hedge funds, commodity houses and brokerage firms. The product covers market abuse detection, best execution analysis, anti-money laundering, and related analytics and reporting. Its models of market risk and market impact are used to detect single-product and cross-product abuse. The company hires in the United Kingdom and Canada.
TradingHub uses Python, C#, C++, Java and .NET with PostgreSQL and DynamoDB, runs on AWS (ECS, CloudFormation) plus Azure and GCP, and uses PyTorch, TensorFlow, scikit-learn and AWS Bedrock for ML.
Yes, engineering and customer support are its main hiring areas, skewed toward senior roles, with smaller openings in data, product and sales. Overall hiring velocity is currently minimal.
TradingHub is headquartered in London, England, and hires in the United Kingdom and Canada.
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TradingHub'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 →
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