Junior / Graduate Data Scientist

Junior / Graduate Data Scientist
Our client, a fast-growing and innovative organisation, is looking for a Junior / Graduate Data Scientist to join their expanding data function.

This is an excellent opportunity for an early-career data professional to gain hands‑on experience across the full machine learning lifecycle in a regulated, real‑world environment. You’ll work closely with Senior Data Scientists, Data Engineers, and Analysts to develop, test, and support production‑ready models using modern cloud technologies.

The Role

You will work primarily with Python, SQL, and AWS (including Amazon SageMaker) to:

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• Extract, transform, and analyse data from AWS data platforms
  
• Perform exploratory data analysis and communicate insights clearly
  
• Build and evaluate baseline machine learning models (classification & regression)
  
• Support model experimentation in Amazon SageMaker Unified Studio
  
• Contribute to model deployment, monitoring, and safe rollout practices
  
• Follow best practices in Git, code review, testing, and Agile delivery
  
• Support data governance, documentation, and privacy‑by‑design principles
  

This role offers structured mentorship and exposure to data science beyond modelling — including productionisation, compliance, and engineering collaboration.

Essential Requirements

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• Degree in a quantitative discipline (Data Science, Computer Science, Maths, Statistics, Physics, Engineering) or equivalent experience
  
• Early career stage (graduate, placement, bootcamp, or personal projects)
  
• Strong Python skills (pandas, scikit‑learn)
  
• Solid SQL skills (joins, aggregations, relational data)
  
• Understanding of ML fundamentals (train/test splits, overfitting, evaluation metrics)
  
• Clear communication skills
  
• Strong learning mindset and interest in AWS/cloud technologies
  
• Comfortable working in a regulated environment
  

Desirable

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• Exposure to Amazon SageMaker
  
• Experience with Jupyter Notebooks
  
• Git and basic software engineering practices
  
• Data visualisation tools (e.g., Power BI)
  
• Financial services data exposure (risk, fraud, payments)
  

What’s on Offer

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• Structured development and mentorship
  
• Hybrid working model
  
• Company pension
  
• 23–28 days holiday + bank holidays
  
• Birthday leave, charity day, wellbeing day, wedding leave
  

Interested? Please Click Apply Now!