Data Scientist

On a data scientist apprenticeship course, you’ll help find information in diverse datasets to address complex problems.

Data science is a broad and fast-growing discipline encompassing mathematics and statistics, software engineering, and communications.

As a data scientist apprentice, you will learn to mine vast amounts of data for information to solve challenging problems and improve organisational processes.

You will actively search out new and innovative ways to utilise existing statistical, algorithmic, predictive, machine learning, and artificial intelligence tools and techniques to discover significant and valuable data patterns and turn them into information for your organisation.

You will apply a scientific approach to perform statistical analysis, build and test models using data, utilise programming methods, and manage data, tools, and processes to provide solid and usable data solutions.

In this role, you must be inquisitive and capable of researching and visualising different data and discovering and presenting relevant “stories” within the data.

What you’ll learn

On a data scientist apprenticeship course, you’ll learn to:

• Identify and explain challenges inside a company, then reformulate them as Data Science problems. 
• Apply scientific methods to experiment design, measurement, hypothesis testing, and dissemination of results. 
• Create and maintain datasets for analysis. Using tools and techniques, source, access, analyse, profile, process, integrate, transform, store data, and apply governance (quality control, security, and privacy) to data.
• Recognise and use an appropriate collection of computer languages and tools for data processing, analysis, visualisation, and system integration. 
• Select the most suitable data structures and methods for the problem. While following software development principles such as security, accessibility, code quality, and version control, create repeatable analysis and robust code.
• Build models and utilise statistical testing to validate the finding.
• Implement data solutions, and use suitable software engineering frameworks and design patterns. 
• Find, display, communicate, and distribute outputs effectively and compellingly, using creative storytelling and tailoring the message to the audience. Use the best medium for each audience, such as technical writing, reporting, and dashboards. Create compelling and actionable tales by using data visualisation. Make recommendations to decision-makers to assist the organisation in achieving its goals.
• Develop and maintain collaborative connections at the strategic and operational levels via the use of organisational empathy methods (human, organisational, and technology) and relationship building through active listening and trust development.

Entry requirements

You’ll usually need:

• Three A-levels, including one science, technology, engineering or mathematics subject, a level 3 apprenticeship, or other relevant qualifications or experience, particularly if strong analytical skills are demonstrated.
• Apprentices without level 2 English and maths will need to achieve this before taking the end-point assessment.

Assessment methods

The End Point Assessment comprises three distinct assessment methods: 

• Knowledge Test, followed by 
• Report (based on a work-based project) and 
• Professional Discussion (informed by a portfolio) 

Duration, level, subjects and potential salary upon completion

Apprenticeship standard

More information about the Level 6 Data Scientist Apprenticeship standard can be found here.

Apprenticeship end point assessment

For more information about the End Point Assessment Process, please read the Institute of Apprenticeships’ information page.