AI Data Analyst Specialist Apprentice

Summary

You will have the opportunity to gain valuable skills, knowledge and experience as you complete a AI Data Analyst - Level 7 Apprenticeship. Duties will include Design and deploy custom AI and automation solutions for SMEs across the UK.

Wage

£20,000 a year

Check minimum wage rates (opens in new tab)

Training course

Artificial intelligence (AI) data specialist (level 7)

Hours

All details will be confirmed at interview.

37 hours 30 minutes a week

Start date

Monday 19 May 2025

Duration

2 years

Positions available

3

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

Assess client needs and implement tailored AI-driven workflows using tools like ChatGPT, Claude, and Botpress.
Automate business processes with platforms like Zapier to enhance efficiency.
Troubleshoot, optimise, and improve AI and automation systems for better performance.
Manage and enhance Envera’s internal AI systems, including customer interaction bots.
Support AI project planning, ensuring smooth deployment and integration of new technologies.
Stay updated on emerging AI trends and contribute ideas for new automation solutions.
Demonstrate problem-solving skills, analytical thinking, and a strong interest in AI and automation.

Where you’ll work

56 Nithsdale Avenue
Market Harborough
LE16 9PE

Training

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

College or training organisation

QA LIMITED

Your training course

Artificial intelligence (AI) data specialist (level 7)

Equal to master’s degree

Course contents

Use applied research and data modelling to design and refine the database & storage architectures to deliver secure, stable and scalable data products to the business
Independently analyse test data, interpret results and evaluate the suitability of proposed solutions, considering current and future business requirements
Critically evaluate arguments, assumptions, abstract concepts and data (that may be incomplete), to make recommendations and to enable a business solution or range of solutions to be achieved
Communicate concepts and present in a manner appropriate to diverse audiences, adapting communication techniques accordingly
Manage expectations and present user research insight, proposed solutions and/or test findings to clients and stakeholders.
Provide direction and technical guidance for the business with regard to AI and data science opportunities
Work autonomously and interact effectively within wide, multidisciplinary teams
Coordinate, negotiate with and manage expectations of diverse stakeholders suppliers with conflicting priorities, interests and timescales
Manipulate, analyse and visualise complex datasets
Select datasets and methodologies most appropriate to the business problem
Apply aspects of advanced maths and statistics relevant to AI and data science that deliver business outcomes
Consider the associated regulatory, legal, ethical and governance issues when evaluating choices at each stage of the data process
Identify appropriate resources and architectures for solving a computational problem within the workplace
Work collaboratively with software engineers to ensure suitable testing and documentation processes are implemented.
Develop, build and maintain the services and platforms that deliver AI and data science
Define requirements for, and supervise implementation of, and use data management infrastructure, including enterprise, private and public cloud resources and services
Consistently implement data curation and data quality controls
Develop tools that visualise data systems and structures for monitoring and performance
Use scalable infrastructures, high performance networks, infrastructure and services management and operation to generate effective business solutions.
Design efficient algorithms for accessing and analysing large amounts of data, including Application Programming Interfaces (API) to different databases and data sets
Identify and quantify different kinds of uncertainty in the outputs of data collection, experiments and analyses
Apply scientific methods in a systematic process through experimental design, exploratory data analysis and hypothesis testing to facilitate business decision making
Disseminate AI and data science practices across departments and in industry, promoting professional development and use of best practice
Apply research methodology and project management techniques appropriate to the organisation and products
Select and use programming languages and tools, and follow appropriate software development practices
Select and apply the most effective/appropriate AI and data science techniques to solve complex business problems
Analyse information, frame questions and conduct discussions with subject matter experts and assess existing data to scope new AI and data science requirements
Undertakes independent, impartial decision-making respecting the opinions and views of others in complex, unpredictable and changing circumstances
Use applied research and data modelling to design and refine the database & storage architectures to deliver secure, stable and scalable data products to the business
Independently analyse test data, interpret results and evaluate the suitability of proposed solutions, considering current and future business requirements
Critically evaluate arguments, assumptions, abstract concepts and data (that may be incomplete), to make recommendations and to enable a business solution or range of solutions to be achieved
Communicate concepts and present in a manner appropriate to diverse audiences, adapting communication techniques accordingly
Manage expectations and present user research insight, proposed solutions and/or test findings to clients and stakeholders.
Provide direction and technical guidance for the business with regard to AI and data science opportunities
Work autonomously and interact effectively within wide, multidisciplinary teams
Coordinate, negotiate with and manage expectations of diverse stakeholders suppliers with conflicting priorities, interests and timescales
Manipulate, analyse and visualise complex datasets
Select datasets and methodologies most appropriate to the business problem
Apply aspects of advanced maths and statistics relevant to AI and data science that deliver business outcomes
Consider the associated regulatory, legal, ethical and governance issues when evaluating choices at each stage of the data process
Identify appropriate resources and architectures for solving a computational problem within the workplace
Work collaboratively with software engineers to ensure suitable testing and documentation processes are implemented.
Develop, build and maintain the services and platforms that deliver AI and data science
Define requirements for, and supervise implementation of, and use data management infrastructure, including enterprise, private and public cloud resources and services
Consistently implement data curation and data quality controls
Develop tools that visualise data systems and structures for monitoring and performance
Use scalable infrastructures, high performance networks, infrastructure and services management and operation to generate effective business solutions.
Design efficient algorithms for accessing and analysing large amounts of data, including Application Programming Interfaces (API) to different databases and data sets
Identify and quantify different kinds of uncertainty in the outputs of data collection, experiments and analyses
Apply scientific methods in a systematic process through experimental design, exploratory data analysis and hypothesis testing to facilitate business decision making
Disseminate AI and data science practices across departments and in industry, promoting professional development and use of best practice
Apply research methodology and project management techniques appropriate to the organisation and products
Select and use programming languages and tools, and follow appropriate software development practices
Select and apply the most effective/appropriate AI and data science techniques to solve complex business problems
Analyse information, frame questions and conduct discussions with subject matter experts and assess existing data to scope new AI and data science requirements
Undertakes independent, impartial decision-making respecting the opinions and views of others in complex, unpredictable and changing circumstances

Your training plan

Apprentices will learn to use a variety of tools and technologies, including:

Statistics and visualistion

Python
Excel
Power BI

Machine learning

Python
Sklearn
NLTK
Tesnorflow & Keras
Cloud services
AWS
Azure
GCP

Foundation models

OpenAI
Hugging Face
Development environments
Google Colab
Anaconda

Alternative environments available.

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

Attention to detail
Organisation skills
Team working
Non judgemental

About this company

As an AI Apprentice at Envera, you will play a key role in managing and developing AI-driven automations both internally within the business and externally for new and existing clients. This role involves working on AI and automation projects for SMEs across the United Kingdom, ensuring the successful deployment of AI solutions that improve efficiency, streamline operations, and enhance business processes.

Company benefits

Flexible Working: Office-based and remote work options available. Professional Development: Ongoing training, AI courses, and industry events. Company Perks: Paid training, team-building events, and career progression opportunities.

After this apprenticeship

This role is designed for individuals who are passionate about AI automation and process optimisation. As Envera continues to grow in the AI space, successful candidates will be positioned to lead and expand automation projects, ensuring businesses across the UK benefit from cutting-edge AI solutions.

Ask a question

The contact for this apprenticeship is:

QA LIMITED

The reference code for this apprenticeship is VAC1000312967.

Apply now

Closes on Monday 5 May 2025

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