Developing data science capability
Training and capability improvement involves identifying and advocating ways to develop the skills, knowledge and performance of individuals or organisations.
Niveaux
- 1. Sensibilisation
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
- 2. Pratique
You can:
- manage your CPD (continuous professional development) and can link your learning to objectives and organisational goals
- confidently talk about the benefits of data science approaches to existing and potential customers
- demonstrate a good understanding of key data science techniques, such as machine learning, and you can use them to build data science solutions, including reports, models and dashboards
- 3. Confirmé
You can:
- manage your CPD (continuous professional development) and can link your learning to objectives and organisational goals
- support data science capability building across the team and wider organisation
- confidently talk about the benefits of data science approaches to existing and potential customers
- demonstrate a good understanding of a range of data science techniques, such as machine learning and natural language processing, and you can use them to build data science solutions, including reports, models and dashboards
- 4. Expert
You can:
- act as a leader or technical specialist, providing detailed support and guidance within the organisation and helping colleagues to develop skills
- set the direction of CPD (continuous professional development) within your team
- keep up to date with new developments in data science and can match those to opportunities in your organisation
- talk confidently about the benefits of data science approaches to existing and potential customers
- demonstrate an in-depth understanding of a wide range of data science techniques, such as machine learning and natural language processing, and detailed knowledge of at least one specialism
- use these techniques to build data science solutions, including reports, models and dashboards
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.
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Contains ESCO v1.2.1 data (https://esco.ec.europa.eu/). © European Union. Reuse authorised under Commission Decision 2011/833/EU.
Niveaux de rôle qui attendent cette compétence
| Niveau de rôle | Rôle | Bande | Niveau attendu |
|---|---|---|---|
| Data scientist en formation | Data scientist | 4 | Sensibilisation |
| Data scientist adjoint | Data scientist | 5 | Pratique |
| Data scientist | Data scientist | 6 | Confirmé |
| Data scientist principal | Data scientist | 7 | Confirmé |
| Data scientist référent | Data scientist | 8a | Expert |
| Responsable de la science des données | Data scientist | 8b | Expert |