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Salary
$73k – $87k per year
Location
Hybrid (London, United Kingdom)
Seniority
Junior · 2+ years exp
Employment
Full-Time

First seen by Alion on Oct 7, 2026.

Overview
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Impact
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We are a hiring consultancy and are determined to make hiring and being hired, a professional, fair and enjoyable experience.

Data Scientist

London (Hybrid, 3 days per week)

Marshall Wolfe are hiring on behalf of our client, a high-growth AI company for a Data Scientist to join their engineering team developing advanced machine learning solutions that help organisations make smarter, data-driven decisions. This role is heavily focused on machine learning, data science and statistics.

This is an excellent opportunity for an ambitious, self-starting individual with a strong academic background in Computer Science, Statistics, Mathematics, Machine Learning, or a related subject. You’ll join a tight, ambitious team of engineers and report into a highly technical leadership group. This is a hands-on role with real ownership, meaningful impact and exposure to cutting-edge ML and agentic AI development.


Key Responsibilities

  • Build, train and optimise machine learning models.
  • Analyse large datasets to identify trends and insights.
  • Develop predictive models for customer behaviour, churn and lifetime value.
  • Apply statistical analysis and experimentation techniques.
  • Collaborate with engineers to deploy and monitor models in production.

Requirements

  • Degree in Computer Science, Statistics, Mathematics, Machine Learning or a related quantitative discipline.
  • Hands-on experience using AI coding agents, such as Codex, Claude, or Cursor, to write and improve code, with the ability to understand, review and test output.
  • Strong Python and SQL skills.
  • 2-5 years commercial experience in Data Science, Analytics or Machine Learning is preferred.
  • Solid understanding of machine learning and statistical modelling.
  • Experience with PyTorch, TensorFlow or similar frameworks would be advantageous.
  • Self-motivated, curious and eager to learn.


You’ll work on real business problems, see your models directly influence customer decisions, and grow quickly in a high-ownership environment. The team is technical, collaborative and values culture fit as much as capability.

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