Artificial intelligence (AI) data specialist (level 7)
Discover new artificial intelligence solutions that use data to improve and automate business processes.
Equivalent to master’s degree
- Typical duration
- 24 months
- Apprenticeship category
- Maximum funding
Maximum amount government will fund
for apprenticeship training.
- Also known as
- AI strategy manager
- Artificial intelligence engineer
- Artificial intelligence specialist
- Director AI
- Machine learning engineer
- Machine learning specialist
Skills an apprentice will learn
- 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
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