Salary: £25,000 - 35,000 per year Requirements: 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 Exposure to Amazon SageMaker (desirable) Experience with Jupyter Notebooks (desirable) Familiarity with Git and basic software engineering practices (desirable) Data visualisation tools experience (e.g., Power BI) (desirable) Financial services data exposure (risk, fraud, payments) (desirable) Responsibilities: 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 Technologies: AWS Cloud Git Support Jupyter Machine Learning Power BI Python SQL pandas More: We are a fast-growing and innovative organization looking for a Junior / Graduate Data Scientist to join our 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. We offer structured mentorship, a hybrid working model, a company pension, and 23–28 days of holiday plus bank holidays. Additional benefits include birthday leave, a charity day, a wellbeing day, and wedding leave. last updated 8 week of 2026