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# Data Scientist

- **Company:** Marshall Wolfe
- **Location:** London, UK
- **Experience:** Experienced
- **Salary:** £55,000.0 - £65,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Big Data, Cursor, Python (Programming Language), Machine Learning, Tensorflow, Standard Sql, Pytorch, AI Coding Agents, Information Technology, Claude
- **Published:** October 7, 2026
- **Apply:** https://www.reed.co.uk/jobs/data-scientist/57430625

## About the Role

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., * 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.
Skills

 * Data Science
 * Machine Learning
 * Python
 * SQL
 * Statistical Analysis
 * Statistical Modeling
 * Statistics

## Description

* 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.