Data Scientist
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Role details
Tech stack
Job 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.
Requirements
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
About the company
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.
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Prepare application
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