Data science innovation

Citée du UK GDaD PCF.

Niveaux

1. Sensibilisation

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

2. Pratique

You can:

• adopt an inquisitive and curious approach to data
• seek out and research new data science techniques to support learning
• ask questions to improve your knowledge and learn about data science norms
• see possibilities for improvements and innovation

3. Confirmé

You can:

• demonstrate practical knowledge of data science tools and techniques
• develop data science solutions that maximise insight
• identify opportunities for how data science can improve data practices

4. Expert

You can:

• be a leader in the data science space
• demonstrate in-depth knowledge of data science tools and techniques, which you can use to solve problems creatively and to create opportunities for your team
• act as a coach, inspiring curiosity and creativity in others
• demonstrate in-depth knowledge of your chosen profession and keep up to date with changes in the industry
• challenge the status quo and always look for ways to improve data science

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.

Compétences ESCO les plus proches

• data science (correspondance proche)
• perform data mining (correspondance étroite)
• innovate in ICT (correspondance étroite)

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