Description

Our client, a leading global macro hedge fund is looking for a Machine Learning Engineer in London to support its Data Science function, working closely with Quant Research, Trading, Risk, and Technology teams. The team operates as a hybrid Data Science and Engineering unit, responsible for designing, building, and deploying data-driven solutions that feed both systematic and discretionary trading strategies, with a focus on large-scale financial and alternative datasets, real-time model pipelines, and advanced analytical tooling.

Responsibilities:

• Develop and deploy machine learning models and time-series forecasting solutions across large-scale financial and alternative datasets
• Partner with Quant Researchers, Portfolio Managers, and Technology teams to deliver data-driven insights and production-grade solutions
• Design and maintain data pipelines processing high-frequency market data, news, and other unstructured datasets
• Apply advanced statistical and machine learning techniques to enhance research and trading strategies
• Build scalable systems that deliver model outputs to multiple stakeholders in real-time environments

Requirements:

• Degree in Computer Science, Engineering, or a quantitative discipline
• 3+ years of hands-on experience in machine learning and statistical modelling on large datasets
• Strong programming skills in Python (preferred) or C++, with experience in distributed data technologies such as Spark/Scala and SQL
• Experience building and deploying production-level systems or models, ideally in containerised environments
• Solid understanding of statistics, optimisation, and time-series analysis, with the ability to communicate findings effectively