Data & AI Apprentice
Mizuho EMEA Corporate Services
London (EC4M 7AU)
Closes on Friday 16 October 2026
Posted on 24 August 2026
Contents
Summary
The Data & AI Apprentice role is an entry-level position within the AI, Data Analytics & Innovation function. It is designed for someone starting their career in data and artificial intelligence, with no prior professional data or AI experience required.
- Wage
-
£28,000 a year
- Training course
- Data analyst (level 4)
- Hours
-
Monday to Friday, usual office hours
37 hours a week
- Start date
-
Monday 2 November 2026
- Duration
-
2 years
- 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 Level 4 Data Analyst Apprentice, you will assist with collecting, organising, cleansing, and validating data from approved internal sources. You will also help produce and maintain dashboards, reports, metrics, and visualisations using approved tools. Furthermore, you will support the identification of suitable AI use cases with business and technology stakeholders, and assist with approved proofs of concept, testing, and evaluation activities.
Through these responsibilities, you will learn how data and AI can be used responsibly to support business insight, operational improvement and better decision-making within a regulated financial-services environment, while developing valuable professional, technical, and communication skills.
Where you'll work
30 Old Bailey
London
EC4M 7AU
Training
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
Training provider
BPP PROFESSIONAL EDUCATION LIMITED
Training course
Data analyst (level 4)
Understanding apprenticeship levels (opens in new tab)
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
- A structured development pathway completing a relevant Level 4 Data Analyst apprenticeship programme.
- Professional training to help build practical knowledge of the data lifecycle, data types, data structures, and the principles of data quality.
Requirements
Desirable qualifications
A Level in:
Share if you have other relevant qualifications and industry experience. The apprenticeship can be adjusted to reflect what you already know.
Skills
- Attention to detail
- Organisation skills
- Problem solving skills
- Administrative skills
- Number skills
- Analytical skills
- Logical
About this employer
Mizuho is not your typical financial institution.
We offer a fantastic opportunity to gain experience within a global investment bank, working on real projects, whilst developing a strong professional network within a bank that prides itself on its inclusive, cooperative and friendly company culture.
We offer the best of both worlds - the feeling of a boutique work environment within a global organisation. Our steady growth in EMEA gives our people at all levels rewarding degrees of responsibility and a richer work experience than a small firm or an established giant could offer alone.
https://www.mizuhogroup.com/ (opens in new tab)
Disability Confident
A fair proportion of interviews for this apprenticeship will be offered to applicants with a disability or long-term health condition. This includes non-visible disabilities and conditions.
You can choose to be considered for an interview under the Disability Confident scheme. You’ll need to meet the essential requirements to be considered for an interview.
After this apprenticeship
Your earnings can increase over time with an apprenticeship. Find out about potential future pay (opens in new tab).
You will have a clear pathway for future career progression within the AI, Data Analytics & Innovation function.
Ask a question
The contact for this apprenticeship is:
Mizuho EMEA Corporate Services
Mizuho-GRB Recruitment Team
mizuho@grb.uk.com
The reference code for this apprenticeship is VAC2000049327.
Apply now
Closes on Friday 16 October 2026
After signing in, you’ll apply for this apprenticeship on the company's website.