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DV Cleared Data Scientist

Posted 5 hours 4 minutes ago by Korn Ferry

Contract
Not Specified
Other
London, United Kingdom
Job Description

Please note, you must hold active DV Clearance and be a sole British national to be eligible for this role.

Responsibilities:

  • Design, develop, and test solutions to collect, integrate, and prepare data for advanced analytics and machine learning applications.
  • Analyse complex datasets to uncover trends, patterns, and actionable insights that drive business or operational outcomes.
  • Build, prototype, and evaluate statistical and machine learning models to solve real-world problems, testing feasibility and estimating impact before full deployment.
  • Engineer and implement ML-based solutions, owning the full life cycle - from model development and deployment to monitoring and iteration.
  • Deploy models into production environments, handling the integration and operationalisation of ML within wider systems and applications.
  • Continuously evaluate and monitor model performance, identifying degradation, performance gaps, or opportunities for optimisation.
  • Collaborate closely with data analysts, engineers, and other stakeholders to define new tools, enhance workflows, and support innovation across teams.

About You:

  • You have a strong foundation in data science, analytics, or machine learning, with hands-on experience developing models that solve practical problems and deliver measurable impact.
  • You are comfortable working across the full machine learning life cycle - from exploratory data analysis and model prototyping to production deployment, integration, and ongoing monitoring.
  • You are proficient in Python and its data/ML ecosystem (eg pandas, scikit-learn, PyTorch, TensorFlow), and you can apply statistical and machine learning techniques confidently in real-world settings.
  • You have deployed models into live systems and understand how to make ML operational - whether that means working with APIs, integrating into existing applications, or using containerisation tools like Docker
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