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Quantitative developer - trade systems, data platform & risk - hedge fund - london

Slough
Attribution Search
Quantitative developer
Posted: 12 April
Offer description

Attribution Search is partnered with a leading global hedge fund, looking to hire Quantitative Developers across both Trading, and Data Platform & Risk Analytics teams.


These roles offer the opportunity to work in a high-performing, front-office environment, building systems that directly support systematic trading, portfolio analytics, and risk management across multiple asset classes.


Responsibilities:

As a member of the team, you will be involved across the full software development lifecycle, working closely with quants, traders, and risk teams to deliver scalable and high-performance solutions.


Depending on team alignment, responsibilities will include:

* Developing and maintaining Python-based tools supporting systematic trading strategies
* Supporting the full lifecycle of trading systems, from research and backtesting through to production deployment and monitoring
* Building and maintaining data platforms and analytics systems covering P&L, VaR, scenarios, and exposure reporting
* Designing and optimising data ingestion, storage, and access layers for large-scale financial datasets
* Developing low-latency components in C# for performance-critical workflows
* Ensuring production systems are reliable, well-tested, and scalable
* Collaborating closely with stakeholders to translate business requirements into technical solutions


Requirements:

* Degree in Computer Science, Mathematics, Engineering, or a related quantitative field
* 5+ years’ experience in quantitative development, software engineering, or data platform roles
* Strong Python experience in a production environment
* Experience working with data pipelines, analytics systems, or trading platforms
* Exposure to high-performance or low-latency systems (C#, Java, or C++)
* Strong SQL skills and experience working with relational databases
* Familiarity with large-scale data processing and time-series datasets
* Experience with messaging systems (e.g. RabbitMQ, Kafka)
* Exposure to modern tooling such as Docker, Kubernetes, and cloud platforms (AWS)
* Understanding of systematic trading environments or financial products is beneficial
* Strong analytical and problem-solving skills
* Excellent communication and ability to work with cross-functional teams


Candidates with relevant experience are encouraged to apply to find out more.

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