Trainee data scientist

Band 4 · Data scientist · 276 job evaluation points

UK GDaD PCF level: Trainee data scientist

Most often performed at Civil Service grade AO or EO.

A trainee data scientist is inquisitive, curious about data and keen to learn and develop.
At this role level, you will:
have a basic understanding of software development and analytical methods
interpret statistical outputs effectively
be aware of how data science techniques can be used, and have a basic knowledge of those key techniques, such as machine learning
work as part of a multidisciplinary team to develop data science solutions and outputs
prepare and manipulate data
present effectively
be aware of ethical considerations
be aware of the technologies used

Contains public sector information from the UK Government Digital and Data Profession Capability Framework (https://understand-digital-data-roles-skills.service.gov.uk/), licensed under the Open Government Licence v3.0. © Crown copyright.

Responsibilities

Learn the team's statistical and machine learning methods, tools, and secure ways of working through structured training.
Prepare and explore pseudonymised health data sets under supervision.
Run and interpret simple statistical analyses, checking results with a more experienced data scientist.
Follow information governance, disclosure control, and ethics procedures.
Work towards a data science apprenticeship or equivalent qualification.

Skills

Skill	Expected level	What this level means
Applied maths, statistics and scientific practicesUK GDaD PCF	Awareness (1)	You can: show an understanding of the benefits of applied mathematics and statistics, and can use this knowledge to carry out data science tasks carry out general analysis techniques for data inspection, exploration and visualisation interpret statistical output effectively and accurately show an awareness of different performance and accuracy metrics for statistical assessment and validation
Data engineeringUK GDaD PCF	Awareness (1)	You can: explain why you need engineering support to design and provide products for the organisation explain why you need to cleanse and prepare data for use in data science products explain different architectures, including cloud and on-premise, and data manipulation and transformation tools
Data ethics and privacyUK GDaD PCF	Awareness (1)	You can: explain the importance of using data ethics and privacy in your work identify appropriate channels to discuss ethical issues, with support
Data science innovationUK GDaD PCF	Awareness (1)	You can: adopt an inquisitive and curious approach to data be receptive to learning about data science and its techniques be unafraid to ask questions and discover what there is to learn
Delivering business impactUK GDaD PCF	Awareness (1)	You can: show an understanding of the organisation and the benefits of data science develop data science products as part of a team create basic visuals and presentations to communicate data science effectively show knowledge of data and analysis and can discuss how to align them to meet user needs
Developing data science capabilityUK GDaD PCF	Awareness (1)	You can: show an awareness of various sources of training and self-directed learning for data science create a CPD (continuous professional development) plan with support from your manager demonstrate a basic understanding of key data science techniques, such as machine learning, and how they can be used
Programming and build (data science)UK GDaD PCF	Awareness (1)	You can: show a basic understanding of software development principles and can write simple scripts under supervision
Understanding product deliveryUK GDaD PCF	Awareness (1)	You can: manage your contribution to tasks to fit in with the work of your wider team
Understanding health and care servicesThis reference	Awareness (1)	You can: describe the main parts of the health and care system and the services the organisation supports explain why patient safety and confidentiality matter in your work
Information governance and data protectionThis reference	Awareness (1)	You can: follow the organisation's rules for handling personal and health information recognise and report a data breach or near miss
Pseudonymisation and disclosure controlThis reference	Awareness (1)	You can: explain the difference between identifiable, pseudonymised, and anonymised data follow the organisation's rules for suppressing small numbers in outputs
Safe and fair AI in health careThis reference	Awareness (1)	You can: explain how a model can harm patients, for example through bias, drift, or over-reliance on its output explain why models need validating on the population they will be used with

Typical qualifications and experience

Enrolled on, or working towards, a data science apprenticeship or equivalent.

Band 4 outline

Knowledge: Detailed knowledge of the work area, typically from a foundation degree, apprenticeship, or equivalent experience.
Autonomy: Works within guidelines; resolves most day-to-day problems; manager available for advice.
Scope: Own work and a defined service or process.
Leadership: May supervise a small team or coordinate others' work.
Accountability: Delivery of a defined service or process.

Job evaluation (illustrative)

Factor	Level	Level summary	Points
Communication and relationship skills	3	Gives routine information needing tact or persuasion, or complex or sensitive information, or straightforward training to groups.	21
Knowledge, training, and experience	4	A range of procedures, mostly non-routine, needing intermediate theory (for example a foundation degree or equivalent experience).	88
Analytical and judgemental skills	3	Judgements on a range of facts or situations needing analysis or comparison of options.	27
Planning and organisational skills	2	Plans straightforward tasks or activities, some ongoing.	15
Physical skills	3	Developed skills needing speed or accuracy, such as advanced keyboard use.	27
Responsibility for patient and client care	1	Helps patients, clients, or relatives during incidental contact.	4
Responsibility for policy and service development	1	Follows policies set by others; may comment on changes.	5
Responsibility for financial and physical resources	1	Takes personal care of equipment and resources used in own work.	5
Responsibility for people	1	Shows own work routines to new or less experienced colleagues.	5
Responsibility for information resources	4	Adapts or designs information systems to others' specifications, or runs information systems for a department as the main duty.	24
Responsibility for research and development	2	Regularly does research, development, trials, or equipment and system testing as part of the job.	12
Freedom to act	2	Follows standard procedures and precedent; someone is usually available to ask; work may be checked.	12
Physical effort	2	Frequent sitting or standing in a restricted position, or occasional light to moderate effort.	7
Mental effort	3	Frequent concentration on unpredictable work, or occasional prolonged concentration.	12
Emotional effort	1	Rare exposure, or occasional indirect exposure, to distressing circumstances.	5
Working conditions	2	Occasional unpleasant conditions, frequent travel or outdoor work, or near-continuous screen use on most days.	7
Total (Band 4: 271 to 325)			276

Knowledge is scored at the level the job needs once training is complete enough to do the work.