Gwyddonydd data cyswllt

You can:

• apply analytical methods including exploratory data analysis and statistical testing to a specific data set, to reach accurate and reliable conclusions
• understand and use different performance and accuracy metrics for model validation in data science projects, hypothesis testing and information retrieval
• compare selected applied mathematics and statistical methods and identify their differences
• access and use the statistical and scientific tools available within the organisation

You can:

• identify the appropriate engineering support to design and provide products for the organisation
• recognise the processes and tools for cleansing and preparing data, and put reusable processes and checks in place
• use different architectures, including cloud and on-premise
• use data manipulation and transformation tools

You can:

• apply fundamental principles of data ethics and privacy in your work under supervision
• share data ethics and privacy risks through appropriate channels

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

You can:

• show an understanding of the organisation and the benefits of data science
• collaborate to help identify user needs and develop and deliver data science products
• communicate effectively and present analysis and visualisations tailored to your audience

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

You can:

• write and test scripts and create basic models in one or more languages
• collaborate on shared codebases, using a variety of methodologies

You can:

• show an awareness of the differences between delivery methods, such as Agile and waterfall, and can propose the most appropriate method to deliver each product
• manage your contribution to tasks to fit in with the work of your wider team

Gallwch:

• ddisgrifio prif rannau'r system iechyd a gofal a'r gwasanaethau y mae'r sefydliad yn eu cefnogi
• egluro pam mae diogelwch cleifion a chyfrinachedd yn bwysig yn eich gwaith

Gallwch:

• cymhwyso egwyddorion diogelu data i'ch gwaith
• cyfrannu at asesiadau o'r effaith ar ddiogelu data
• ymdrin â cheisiadau am wybodaeth a chofnodion yn gywir

Gallwch:

• gweithio gyda data wedi'i ffugenwi a chymhwyso gwiriadau datgelu cyn rhyddhau allbynnau
• adnabod pan allai data cysylltiedig neu fanwl adnabod claf

Gallwch:

• egluro sut y gall model niweidio cleifion, er enghraifft drwy duedd, drifft, neu ddibynnu gormod ar ei allbwn
• egluro pam mae angen dilysu modelau ar y boblogaeth y byddant yn cael eu defnyddio gyda hi

Gallwch:

• egluro'r gwahaniaeth rhwng terminoleg glinigol a dosbarthiad
• adnabod terminolegau cyffredin fel SNOMED CT ac ICD