Machine Learning Quant Engineer

Michael Page (UK)
City of London
3 months ago
Applications closed

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  • Up to £1200 per day. Based in Central London
  • Machine Learning Engineer with Quant experience.
About Our Client

The hiring organisation is a large entity within the financial services industry.

Job Description
  • Design and implement machine learning models for financial applications, with a focus on derivatives pricing, risk analytics, and market forecasting.
  • Build scalable ML pipelines to process large volumes of financial data efficiently.
  • Develop deep learning architectures for time series prediction, anomaly detection, and pattern recognition in market data.
  • Optimise model performance using techniques such as hyper-parameter tuning, ensemble methods, and neural architecture search.
  • Collaborate with quantitative analysts to align ML models with pricing methodologies and identify opportunities for innovation.
  • Support the deployment of ML solutions into production systems for real-time risk management and pricing automation.
The Successful Applicant
  • Advanced Machine Learning Expertise - Demonstrates deep understanding of ML algorithms (supervised, unsupervised, reinforcement learning) and has hands-on experience with deep learning architectures like RNNs, LSTMs, and Transformers.
  • Strong Financial Domain Knowledge - Understands financial instruments, derivatives, and risk management principles, with experience applying ML in trading, pricing, or risk analytics contexts.
  • Technical Proficiency - Expert in Python and familiar with ML frameworks such as PyTorch, TensorFlow, and JAX. Skilled in using tools like scikit-learn, XGBoost, and LightGBM.
  • Data Engineering & Infrastructure Skills - Comfortable working with big data technologies (Spark, Dask), SQL/NoSQL databases, and cloud platforms (AWS, GCP, Azure). Able to build scalable ML pipelines for large-scale financial data.
  • Model Optimisation & Deployment Experience - Proven track record of deploying ML models at scale, with experience in hyper-parameter tuning, ensemble methods, and neural architecture search.
  • Collaborative & Business-Focused - Works effectively with quants and stakeholders to translate financial requirements into ML solutions. Communicates insights clearly and aligns models with strategic business goals.
  • Innovative & Analytical Mindset - Capable of developing data-driven approaches that complement traditional quantitative models and drive measurable impact in pricing and risk analytics.
What\'s on Offer
  • A competitive daily rate up to £1200 per day (inside IR35), depending on experience.
  • The opportunity to work on cutting-edge machine learning projects in the financial services industry.
  • A temporary role offering valuable exposure to a global organisation in London.
  • BASED 4 DAYS PER WEEK IN THE OFFICE (Central London)


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