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# Graduate Data Scientist

- **Company:** Give A Grad A Go Ltd
- **Location:** London, UK
- **Experience:** Starter
- **Salary:** £30,784.0
- **Contract:** Temporary to permanent
- **Skills:** Java (Programming Language), Computer Programming, Continuous Integration, Integrated Development Environments, Python (Programming Language), Machine Learning, SQL Databases, Feature Engineering, Pyspark, Information Technology, Data Analytics, Data Pipelines
- **Published:** May 20, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=6f3fcec347b4fa85

## About the Role

Do you have experience in Scala?, Do you have a Master's degree?, As a Graduate Data Scientist, you'll gain hands-on experience with real player data and cutting-edge technology, helping build products that reach millions. If you're curious, collaborative, and ready to make an impact, this is the place to learn fast and grow faster., * A 2:1 degree in mathematics, statistics, computer science, software, engineering or similar (a post-graduate master's degree or PhD is an advantage).

 * Knowledge of data concepts like cleansing, preparing, pipelines, orchestration.
 * Programming skills in any of the following languages: Python, Pyspark, Java, SQL or Scala.
 * Excellent verbal & written communication and presentation skills.
 * A genuine interest and passion within Technology and Data.
 * Organised and proactive, with strong attention to detail and an ability to prioritise effectively
 * This is a 3-month placement with the potential to go permanent.

## Description

In this Graduate Data Scientist role, you will be:

 * Working on cloud platforms and Anthemetrics processing 400 million transactions daily.
 * Assist in building, maintaining and optimising complex data pipelines in a CI/CD development environment, ensuring products are robust, reliable, and fast.
 * Work on Safer Play and Data-Driven Design products, using advanced ML modelling technology to detect gambling markers of harm in real-time.
 * Be a part of an agile scrum team and participate in all ceremonies.
 * Collaborate closely with data science, platform, product, and broader business teams.
 * Gain exposure to how we develop a range of machine learning models via the full lifecycle process (business understanding, feature engineering, prototyping, training, evaluation).


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