Ledende dataforsker

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

Du kan:

• analysere, hvordan en service indgår i patientforløb på tværs af organisationer
• arbejde sammen med klinikere, plejepersonale og patienter om at forme digitale services
• forklare virkningen af digitale beslutninger på pleje, sikkerhed og medarbejdernes arbejdsbyrde

Du kan:

• lede konsekvensanalyser vedrørende databeskyttelse og aftaler om deling af oplysninger
• rådgive teams om retligt grundlag, samtykke, fortrolighed og opbevaring
• undersøge hændelser og anbefale forbedringer

Du kan:

• designe metoder til pseudonymisering og sammenkædning, der holder identifikatorer adskilt fra analysedata
• vurdere risikoen for genidentifikation i et datasæt eller en publikation og vælge egnede kontroller
• rådgive teams om sikre miljøer, såsom betroede forskningsmiljøer

Du kan:

• planlægge validering, vurdering af skævhed og løbende overvågning af en model sammen med kliniske kolleger
• afgøre, hvornår en model skal trænes om, begrænses eller trækkes tilbage
• rådgive teams om, hvornår en model kan være reguleret som medicinsk udstyr, og hvilken evidens den kræver

Du kan:

• deltage i farerworkshops og bidrage til et fareregister
• følge processen for klinisk risikostyring i dit arbejde
• levere dokumentation til en klinisk sikkerhedsbegrundelse, såsom testresultater

Du kan:

• følge en proces for softwarens livscyklus, der opfylder standarderne for medicinsk udstyr
• udarbejde de registre, som en sådan proces kræver

Du kan:

• have personaleansvar for et team, fastsætte mål og gennemføre medarbejdersamtaler
• støtte trivsel og håndtere fravær, præstation og adfærd
• planlægge teamets udvikling og efterfølgelse