Gwyddonydd data arweiniol

You can:

• identify opportunities to develop statistical insight, reports and models to support organisational objectives, while collaborating across the organisation effectively
• critique statistical analyses
• use a variety of data analytics techniques (such as data mining and prescriptive and predictive analytics) for complex data analysis through the whole data life cycle
• use model outputs to produce evidence and help design services and policies
• understand a broad range of statistical tools, particularly those deployed within the organisation, and can use these appropriately and help others to use them

You can:

• help to identify the data engineering requirements for any data science product, while working with data engineers and data scientists to design and deliver those products into the organisation effectively
• understand the need to cleanse and prepare data before including it in data science products and can put reusable processes and checks in place
• understand a broad range of architectures, including cloud and on-premise, and data manipulation and transformation tools deployed within the organisation, and can use these tools appropriately and help others use them

You can:

• oversee compliance with data ethics standards and legislation across the organisation
• develop, manage and continuously improve an ethical framework within your area
• develop a data ethics culture, influencing others to act on it
• ensure data ethics is applied appropriately when formulating, implementing and evaluating organisational policies and programmes

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

You can:

• champion the role of data science within the organisation
• understand and champion user research, and can design and manage processes to gather and establish user needs
• identify and create opportunities to develop and deliver data science products to support organisational objectives, while collaborating across the organisation to fulfil meaningful goals
• take responsibility for delivering scalable data science products into the organisation, and establishing maintenance support

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

You can:

• write complex programs and scripts
• seek to make code open source where appropriate
• supervise junior analysts and set coding standards for your team
• understand software architecture and how to write efficient, optimised code
• perform user testing on products prior to launch

You can:

• understand the differences between delivery methods, such as Agile and waterfall, and can set out how your team should use and adapt these methods
• lead a team through the different phases of the product delivery life cycle
• collaborate with the product manager to influence the direction of work
• identify and involve relevant teams to smoothly deliver data science products into the organisation, ensuring these products inform decision making
• ensure products are monitored, maintained and continually improved, engaging and working with others where necessary
• have oversight of any data science features implemented within products or services

Gallwch:

• dadansoddi sut mae gwasanaeth yn ffitio i lwybrau gofal ar draws sefydliadau
• gweithio gyda chlinigwyr, staff gofal, a chleifion i lunio gwasanaethau digidol
• egluro effaith penderfyniadau digidol ar ofal, diogelwch, a llwyth gwaith staff

Gallwch:

• arwain asesiadau o'r effaith ar ddiogelu data a chytundebau rhannu gwybodaeth
• cynghori timau ar sail gyfreithlon, cydsyniad, cyfrinachedd, a chadw
• ymchwilio i ddigwyddiadau ac argymell gwelliannau

Gallwch:

• dylunio dulliau ffugenwi a chysylltu sy'n cadw dynodwyr ar wahân i ddata dadansoddi
• asesu risg ailadnabod set ddata neu gyhoeddiad a dewis mesurau rheoli addas
• cynghori timau ar leoliadau diogel, fel amgylcheddau ymchwil dibynadwy

Gallwch:

• cynllunio dilysu model, asesu tuedd, a monitro byw gyda chydweithwyr clinigol
• penderfynu pryd mae angen ailhyfforddi, cyfyngu, neu dynnu model yn ôl
• cynghori timau ar pryd y gallai model gael ei reoleiddio fel dyfais feddygol a pha dystiolaeth sydd ei hangen arno

Gallwch:

• cymryd rhan mewn gweithdai peryglon a chyfrannu at log peryglon
• dilyn y broses rheoli risg glinigol ar gyfer eich gwaith
• darparu tystiolaeth ar gyfer achos diogelwch clinigol, fel canlyniadau profion

Gallwch:

• dilyn proses cylch bywyd meddalwedd sy'n bodloni safonau dyfeisiau meddygol
• cynhyrchu'r cofnodion y mae proses o'r fath yn eu gofyn

Gallwch:

• rheoli tîm yn llinell, gan osod amcanion a chynnal arfarniadau
• cefnogi llesiant a rheoli presenoldeb, perfformiad, ac ymddygiad
• cynllunio datblygiad y tîm a chynllunio olyniaeth