AI Data Scientist Apprentice
o-x.ai (ZK Analytics)
Recruiting nationally
Closes in 13 days (Friday 22 August 2025 at 11:59pm)
Posted on 8 August 2025
Contents
Summary
Join o-x.ai as a Degree (Master’s Level) Apprentice in AI & Data Science, building cutting-edge tools for social research and evaluation. Gain hands-on experience in NLP, machine learning, and data analysis on real-world projects for governments and international organisations, whilst earning a Master ’s-level qualification with NU London.
- Wage
-
£15,704 to £25,396.80, depending on your age
National Minimum Wage
Check minimum wage rates (opens in new tab)
Salary from £20,000 to £25,000
- Training course
- Artificial intelligence (AI) data specialist (level 7)
- Hours
-
Monday to Friday.
Occasional work outside of these hours may be required.
40 hours a week
- Start date
-
Monday 29 September 2025
- Duration
-
1 year 9 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
- Analyse quantitative and qualitative datasets for social research and evaluation projects.
- Apply machine learning and natural language processing methods.
- Develop and deploy data pipelines and analytical tools.
- Collaborate with research and technical teams to produce research findings and translate these to clear, actionable insights.
- Identify best practices in AI data systems, whilst ensuring data quality, documentation, and reproducibility throughout workflows.
Where you'll work
Remote
Training
Apprenticeships include time away from working for specialist training. You’ll study to gain professional knowledge and skills.
Training provider
NORTHEASTERN UNIVERSITY-LONDON
Training course
Artificial intelligence (AI) data specialist (level 7)
Understanding apprenticeship levels (opens in new tab)
What you'll learn
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
Training schedule
Requirements
Essential qualifications
Degree in:
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
- Team working
- Initiative
- Statistics concepts
- Awareness of AI
- Machine learning
- Data Analysis
- Proficient with new software
Other requirements
Confident in Python or R in a data setting. Awareness of machine learning i.e logistic or linear regression. Knowledge of data analysis and development tools in Python and R, such as integrated development environments, data manipulation and visualisation libraries, machine learning packages, testing frameworks, and SQL/NoSQL databases. Some applicants may not have traditional qualifications but have relevant skills and experience from work or other learning — these will be considered on a case-by-case basis.
About this employer
o-x.ai specialises in advancing the use of AI and data science for social research and evaluation. We are social researchers, statisticians and data scientists with decades of experience delivering rigorous research and analytics across policy, evaluation, and evidence for the public sector. Our flagship service, signAl™, is a purpose-built AI engine for social research and evaluation. It combines natural language processing, machine learning, and domain expertise to process vast volumes of qualitative and mixed-method data with speed, accuracy, and transparency. Already deployed in high-stakes projects for governments and international organisations, signAl™ enables institutions to scale analysis, accelerate delivery, and uphold the highest standards of methodological rigour.
After this apprenticeship
Successful apprentices may be offered a follow on role with o-x.ai depending on business needs. The skills developed on this programme are in high demand across the public sector, opening opportunities in data science, social research, and policy evaluation roles.
Ask a question
The contact for this apprenticeship is:
NORTHEASTERN UNIVERSITY-LONDON
The reference code for this apprenticeship is VAC1000336244.
Apply now
Closes in 13 days (Friday 22 August 2025 at 11:59pm)
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