Machine Learning Quantitative Researcher

1 month ago

London, Greater London, United Kingdom Campbell North Full time
Job Opportunity

Job Title: Machine Learning and Quantitative Analyst

Locations: Global

Overview:

Campbell North is offering a unique opportunity to collaborate with world-renowned machine learning researchers and former academics on challenging, real-world problems within the field of quantitative finance.

In this role, you will build state-of-the-art algorithms and deploy them on massive datasets containing trillions of observations, receiving immediate feedback on your models and optimisations. You will be supported by a team of top-tier engineers and a cutting-edge tech stack, including a rapid-feedback platform for ML experimentation.

Key Responsibilities:

  • Develop and deploy advanced machine learning and deep learning models to tackle complex problems in quantitative finance.
  • Conduct large-scale data analysis and build ML/DL algorithms optimised for trillions of observations.
  • Experiment with model architectures, feature transformations, and hyperparameter tuning to ensure robust, reliable inferences.
  • Collaborate with both in-house researchers and leading academics to shape the future of ML/DL in finance.
  • Stay active in the academic community by attending and presenting at top conferences.
  • Engage in a culture of continuous learning through study groups, paper discussions, and guest speaker events.

Qualifications:

  • PhD in a quantitative subject (Physics, Biostatistics, Mathematics, Statistics, Computer Science, Engineering, etc.) from a top-tier university.
  • Strong publication record with first-author contributions in leading journals and conferences.
  • Proven coding expertise in Python, C++, or R.
  • Deep knowledge of machine learning / deep learning / NLP techniques and frameworks, with practical experience in applying them to real-world problems.

If you think you might be a good fit, please share your resume with us.

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