Data analyst

You can:

• support the development of statistical and analytical insights and reports under supervision
• explain the benefits of basic statistical and analytical techniques
• explain the value of quality assurance and best practices in developing statistical and analytical outputs

You can:

• explain why it's important to communicate technical concepts in non-technical language
• explain the types of communication that can be used with internal and external stakeholders, and their impact

You can:

• explain the importance of using data ethics and privacy in your work
• identify appropriate channels to discuss ethical issues, with support

You can:

• explain the importance of data governance policies
• explain how data management tools, procedures and methods relate to a specific project

You can:

• explain the importance of data models and their uses
• identify appropriate channels in your organisation to learn about data modelling and quality standards
• identify data quality issues and provide possible solutions to resolve them
• prepare and cleanse data under supervision, contributing to making it fit for purpose

You can:

• develop and use an appropriate data visualisation under supervision to tell a meaningful story that is relevant to set goals
• explain the value of sharing a story effectively
• explain why it's important to develop inclusive, accessible data visualisations that recognise different user needs

You can:

• explain the importance of coding for analysis
• explain the value of maintaining analytical approach documentation
• design an analytical approach with support, for example, writing simple code

You can:

• show an awareness of project management techniques, and an appreciation of how they are applied in the environment

You can:

• contribute to the development of statistical and analytical insights and reports
• apply appropriate statistical and analytical techniques under supervision to answer research questions and organisational needs
• follow and apply quality assurance standards
• respond to stakeholder questions about analytical and statistical techniques

You can:

• communicate effectively with technical and non-technical stakeholders
• support and host discussions within a multidisciplinary team, with potentially difficult dynamics
• be an advocate for the team externally
• manage differing stakeholder perspectives

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:

• follow organisational data governance, including policies on data access, sharing, dissemination and protection
• participate in or deliver data management across services or products
• use appropriate data management tools, procedures and methods with some support

You can:

• support the planning of a data model based on appropriate data sources
• help ensure new and existing data models and pipelines can be reused or reproduced
• identify and resolve data quality issues
• prepare and cleanse data, ensuring it is fit for purpose

You can:

• use the most appropriate data visualisation to tell a focussed story that is relevant to the team's goals
• develop inclusive, accessible data visualisations that recognise different user needs
• work with others in a multidisciplinary team to ensure a visualisation provides the information they need

You can:

• design the analytical approach and the code needed to address simple research questions
• explain the importance of testing code
• review and improve analytical approaches under supervision, including code
• produce analytical approach documentation that describes the code you wrote

You can:

• apply your knowledge and experience of project management methodologies, including tools and techniques
• adopt those most appropriate for the environment

You can:

• lead the development of valuable statistical insights and reports
• identify and apply a range of statistical and analytical techniques and tools, and support others in applying them
• quality assure statistical techniques and analytical outputs across a team
• engage with stakeholders and share statistical and analytical techniques to increase understanding and trust

You can:

• listen to and interpret the needs of technical and non-technical stakeholders, and manage their expectations
• manage active and reactive communication
• support or host difficult discussions within the team or with diverse senior stakeholders

You can:

• work with stakeholders to identify and address ethical and privacy concerns
• demonstrate and communicate how data ethical issues fit into the wider organisational context
• research developments in data ethics and privacy to improve compliance and processes
• assess and constructively challenge proposed data ethics policies

You can:

• advocate for effective data governance and data management policies and guidelines within your team and across your organisation
• monitor and improve data management practices in your team
• help define, develop and support the use of data management tools, procedures and methods in compliance with data governance policies

You can:

• plan the framework of an analytical data model based on appropriate data sources
• support the implementation of data models using appropriate tools and systems
• ensure your team understands the importance of data quality and modelling

You can:

• use a range of data visualisations to simplify a complex story
• adapt a story to the needs of multidisciplinary stakeholders
• advise and support others in developing inclusive, accessible data visualisations that recognise different user needs
• suggest improvements to data visualisation processes and standards to increase efficiency and quality

You can:

• design and implement the analytical approach, including code, using appropriate standards and tests
• lead collaboration to review and improve analytical approaches, including shared code
• guide others in producing analytical approach documentation, identifying improvements

You can:

• share knowledge and experience of project management methodologies with others, including tools and techniques
• define those most appropriate for the environment
• oversee projects within a data analytics team

You can:

• identify opportunities to develop statistical insights and reports that support organisational objectives
• develop and guide others in a range of statistical and analytical techniques and tools
• oversee the quality assurance of statistical techniques and analytical outputs, continually improving and innovating practices
• use statistical and analytical outputs to influence stakeholders across the organisation and beyond

You can:

• mediate between people and strengthen relationships, adopting the appropriate communication method with stakeholders at all levels
• manage stakeholder expectations and moderate difficult discussions about high risk and complex topics, even within constrained timescales
• speak on behalf of, and represent the community to, large audiences inside and outside the organisation

You can:

• work with stakeholders to identify and address ethical and privacy concerns
• demonstrate and communicate how data ethical issues fit into the wider organisational context
• research developments in data ethics and privacy to improve compliance and processes
• assess and constructively challenge proposed data ethics policies

You can:

• champion and lead data management and governance processes within your team and across your organisation
• define and lead on the implementation of data management responsibilities
• define data management tools and develop training requirements to implement data governance processes effectively
• enable continuous improvement of data management practices and compliance with data governance policies

You can:

• develop analytical data models using a deep understanding of data sources
• ensure data models are implemented using tools and systems that align with modelling standards
• set data quality standards in the organisation or beyond, and ensure stakeholders understand their importance
• mentor others in data quality and modelling

You can:

• translate business requirements into goals for data visualisations
• set and advocate for new standards and practices in inclusive, accessible data visualisation
• identify data visualisation capability gaps and implement appropriate training
• promote the value and adoption of data visualisations across the organisation
• strategically support stakeholders in understanding and using a story

You can:

• oversee and promote the implementation of coding standards and practices on existing and new analytical outcomes, products and services
• contribute to coding standards across the organisation
• ensure reproducibility of code and code documentation across the organisation

You can:

• demonstrate knowledge and experience of the application of project management methodologies
• be a recognised specialist and adviser in project management, including user needs, generation of ideas, methods and tools, and leading or guiding others in best practice
• oversee projects within a data analytics team

Communicating between the technical and non-technical

Data management

Data ethics and privacy

Communicating between the technical and non-technical

Data ethics and privacy

Communicating between the technical and non-technical

Data ethics and privacy

Communicating between the technical and non-technical

Communicating between the technical and non-technical