Data Analyst Apprenticeship - Level 4 - BBC Studios - Business and Legal Affairs - London

BBC Public Service
London

Summary

Kickstart your data career with the BBC Studios as a Data Analyst apprentice. Learn Python, Excel and more while working on real projects in a collaborative team. Gain skills in machine learning, data ethics and visualisation, helping shape the BBC’s data-driven future in governance and privacy.

Wage

£22,950 a year

Training course
Data analyst (level 4)

Hours
18 months - 35 hours per week. Days and shifts TBC.

35 hours a week

Start date

Tuesday 8 September 2026

Duration

1 year 6 months

Positions available

1

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

As a Data Analyst apprentice, this is brilliant opportunity to learn, grow, and contribute – you will:

  • Play a key part in driving digital growth through actionable data insights.
  • Collaborate with editorial teams to shape the future of BBC Sport’s digital presence, contributing to major sports tournaments, and support our SEO strategy.
  • Have the opportunity to present findings and recommendations to senior management, helping to inform strategic decisions at the highest level.
  • Data Processing with Pandas.
  • Data Visualisation.
  • Power BI and Tableau.
  • Data Science for Business.
  • Databases & SQL.
  • Text Mining.
  • Introduction to Machine Learning.
  • Time Series Analysis.
  • Data Privacy, Ethics & Regulations.

Where you'll work

New Broadcasting House
Portland Place
London
W1A 1AA

Training

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

Training provider

CAMBRIDGE SPARK LIMITED

Training course

Data analyst (level 4)

What you'll learn

Course contents

  • Use data systems securely to meet requirements and in line with organisational procedures and legislation including principles of Privacy by Design
  • implement the stages of the data analysis lifecycle
  • apply principles of data classification within data analysis activity
  • analyse data sets taking account of different data structures and database designs
  • assess the impact on user experience and domain context on data analysis activity
  • identify and escalate quality risks in data analysis with suggested mitigation or resolutions as appropriate
  • undertake customer requirements analysis and implement findings in data analytics planning and outputs
  • identify data sources and the risks and challenges to combination within data analysis activity
  • apply organizational architecture requirements to data analysis activities
  • apply statistical methodologies to data analysis tasks
  • apply predictive analytics in the collation and use of data
  • collaborate and communicate with a range of internal and external stakeholders using appropriate styles and behaviours to suit the audience
  • use a range of analytical techniques such as data mining, time series forecasting and modelling techniques to identify and predict trends and patterns in data
  • collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs
  • select and apply the most appropriate data tools to achieve the optimum outcome
  • Use data systems securely to meet requirements and in line with organisational procedures and legislation including principles of Privacy by Design
  • implement the stages of the data analysis lifecycle
  • apply principles of data classification within data analysis activity
  • analyse data sets taking account of different data structures and database designs
  • assess the impact on user experience and domain context on data analysis activity
  • identify and escalate quality risks in data analysis with suggested mitigation or resolutions as appropriate
  • undertake customer requirements analysis and implement findings in data analytics planning and outputs
  • identify data sources and the risks and challenges to combination within data analysis activity
  • apply organizational architecture requirements to data analysis activities
  • apply statistical methodologies to data analysis tasks
  • apply predictive analytics in the collation and use of data
  • collaborate and communicate with a range of internal and external stakeholders using appropriate styles and behaviours to suit the audience
  • use a range of analytical techniques such as data mining, time series forecasting and modelling techniques to identify and predict trends and patterns in data
  • collate and interpret qualitative and quantitative data and convert into infographics, reports, tables, dashboards and graphs
  • select and apply the most appropriate data tools to achieve the optimum outcome

Training schedule

You’ll study for your industry recognised apprenticeship qualification, learning both on and off the job.?This means you’ll spend at least one day a week studying for a Level 4 Data Analyst qualification from our external Learning Provider.
You will be supported with career development, employability training, and networking opportunities to help you take your next step within the BBC or elsewhere in the industry.

Requirements

Essential qualifications

GCSE in:

English and Maths (grade 4/C or above)

A Level in:

A Level/Higher Maths, or Equivalent Qualification (grade Achieved)

Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.

Skills

  • Communication skills
  • IT skills
  • Attention to detail
  • Organisation skills
  • Problem solving skills
  • Administrative skills
  • Number skills
  • Analytical skills
  • Logical
  • Team working
  • Creative
  • Initiative
  • Non judgemental
  • Patience
Posted 2025-11-06

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