AI Apprentice

Summary

About the Role** As an AI Apprentice, you will have the unique opportunity to learn directly from our team of AI researchers, engineers, and data scientists. This role is designed to provide structured, real-world experience in machine learning, data processing, and model deployment while working on exciting projects.

Annual wage: £13,312 a year
Minimum wage rates (opens in new tab)
Training course: Data analyst (level 4)
Hours: Monday to Friday 9am to 5pm.
40 hours a week
Possible start date: Sunday 5 January
Duration: 2 years
Positions available: 2

Work

As an apprentice, you’ll work at a company and get hands-on experience. You’ll gain new skills and work alongside experienced staff.

What you’ll do at work

Key Responsibilities:

Assist with data collection, preprocessing, and cleaning tasks
Support the development and training of machine learning models
Collaborate on AI research projects under the guidance of senior AI engineers
Perform exploratory data analysis to identify patterns and trends
Document project milestones, coding progress, and learnings
Work with cutting-edge AI technologies like neural networks, natural language processing, and computer vision
Participate in regular team meetings and brainstorming sessions

Where you’ll work

FRASER HOUSE

56 KINGSTON ROAD

STAINES UPON THAMES

TW18 4LN

Training

An apprenticeship includes regular training with a college or other training organisation. At least 20% of your working hours will be spent training or studying.

College or training organisation

SWARM APPRENTICESHIPS C.I.C

Your training course

Data analyst (level 4)

Equal to higher national certificate (HNC)

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

Your training plan

This training plan has not been finalised. Check with this employer if you’ll need to travel to a college or training location for this apprenticeship.

Requirements

Let the company know about other relevant qualifications and industry experience you have. They can adjust the apprenticeship to reflect what you already know.

Skills

Communication skills
IT skills
Attention to detail
Organisation skills
Analytical skills
Logical
Team working
Creative

About this company

About Scrumconnect Consulting: Scrumconnect Consulting, a multi-award-winning firm recognized with UKIT awards such as Best Public Sector IT Project, Digital Transformation Project of the Year, and a Special Award for Organisational Excellence during the pandemic, is at the forefront of innovation in tech consulting. Our work impacts over 40 million UK citizens, with successful projects in key government departments like the Department for Work and Pensions, Ministry of Justice, HM Passport Office, and more.

After this apprenticeship

Data analyst.

Ask a question

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