2027 Data Science Apprentice - Crawley

THALES UK LIMITED
Crawley (RH10 9HA)
Closes on Wednesday 17 February 2027

Posted on 5 October 2026

Summary

As a Data Scientist Apprentice, you will be valued for your curiosity, analytical mindset, and passion for solving problems using data. You will work with a variety of datasets, tools, and technologies to identify trends, build predictive models, and generate insights that support business decision-making.

Wage: £24,000 a year

Minimum wage rates (opens in new tab)

• Pension – Thales match, plus 1%, with a maximum contribution of 7%
• Health Insurance – 50% of salary for five years
• Performance-related pay uplifts

Training

Training course: Data scientist (integrated degree) (level 6)
Hours: Monday - Friday (8 hours Monday – Thursday, 5 hours Friday). Shifts TBC. 37 hours a week
Start date: Monday 6 September 2027
Duration: 3 years 6 months
Positions available: 2

Work

Most of your apprenticeship is spent working. You’ll learn on the job by getting hands-on experience.

What you'll do at work

Working alongside experienced data professionals, you will learn how to transform raw data into valuable business intelligence and help develop data-driven solutions that create measurable impact. Your responsibilities may include:

• Identifying business challenges and using data science techniques to recommend solutions.
• Collecting, preparing, cleansing, and analysing data from multiple sources.
• Building skills in:
  • Data Science and Analytics
  • Machine Learning and Artificial Intelligence
  • Statistical Analysis
  • Data Engineering Fundamentals
  • Data Visualisation and Storytelling
  • Programming and Automation (e.g. Python, SQL)
• Supporting the development and testing of predictive models and analytical solutions.
• Working with data teams to create data products, dashboards, and insights used across the business.
• Evaluating model performance and supporting continuous improvement of analytical solutions.

Where you'll work

Manor Royal
Crawley RH10 9HA

Training

Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.

Training provider: UNIVERSITY OF NOTTINGHAM

Training course: Data scientist (integrated degree) (level 6)

What you'll learn

• Identify and clarify problems an organisation faces, and reformulate them into Data Science problems.
• Devise solutions and make decisions in context by seeking feedback from stakeholders.
• Apply scientific methods through experiment design, measurement, hypothesis testing and delivery of results.
• Collaborate with colleagues to gather requirements.
• Perform data engineering: create and handle datasets for analysis.
• Use tools and techniques to source, access, explore, profile, pipeline, combine, transform and store data, and apply governance (quality control, security, privacy) to data.
• Identify and use an appropriate range of programming languages and tools for data manipulation, analysis, visualisation, and system integration.
• Select appropriate data structures and algorithms for the problem.
• Develop reproducible analysis and robust code, working in accordance with software development standards, including security, accessibility, code quality and version control.
• Use analysis and models to inform and improve organisational outcomes, building models and validating results with statistical testing: perform statistical analysis, correlation vs causation, feature selection and engineering, machine learning, optimisation, and simulations, using the appropriate techniques for the problem.
• Implement data solutions, using relevant software engineering architectures and design patterns.
• Evaluate Cloud vs. on-premise deployment.
• Determine the implicit and explicit value of data.
• Assess value for money and Return on Investment.
• Scale a system up/out.
• Evaluate emerging trends and new approaches.
• Compare the pros and cons of software applications and techniques.
• Find, present, communicate and disseminate outputs effectively and with high impact through creative storytelling, tailoring the message for the audience.
• Use the best medium for each audience, such as technical writing, reporting and dashboards.
• Visualise data to tell compelling and actionable narratives.
• Make recommendations to decision makers to contribute towards the achievement of organisation goals.
• Develop and maintain collaborative relationships at strategic and operational levels, using methods of organisational empathy (human, organisation and technical) and build relationships through active listening and trust development.
• Use project delivery techniques and tools appropriate to their Data Science project and organisation.
• Plan, organise and manage resources to successfully run a small Data Science project, achieve organisational goals and enable effective change.