Junior / Graduate Data Scientist

Adria Solutions ltd
Manchester, United Kingdom
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Junior
Compensation
£ 35K

Job location

Manchester, United Kingdom

Tech stack

Agile Methodologies
Amazon Web Services (AWS)
Data analysis
Cloud Computing
Code Review
Data Governance
Data Visualization
Relational Databases
Python
Machine Learning
Power BI
Software Engineering
SQL Databases
Jupyter Notebook
GIT
Pandas
Scikit Learn
Information Technology
Data Management

Job description

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

  • 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.

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

Desirable

  • 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)

Benefits & conditions

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

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