数据分析师

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:

• explain how your work aligns to the organisation's priorities and delivers business impact
• work with others to help identify business requirements
• identify the data needed to address business requirements
• develop and deliver data products that align to organisational priorities and enable decision making, with some support when required

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:

• contribute to defining problem statements and gathering project requirements
• explain the importance of different processes and stages of the data project life cycle and contribute to their planning
• adapt your ways of working to deliver different project outcomes and requirements

您可以：

• 解释您的工作所支持的临床和照护工作流程
• 与临床和照护同事正确使用常见的医疗卫生术语
• 识别某项变更何时可能影响患者照护并提出来

您可以：

• 在工作中应用数据保护原则
• 为数据保护影响评估作出贡献
• 正确处理信息请求和记录

您可以：

• 运行数据质量检查并纠正错误
• 向同事解释数据质量报告

您可以：

• 使用假名化数据，并在发布输出前进行披露检查
• 识别关联数据或详细数据何时可能识别出某位患者

您可以：

• 为数据项或表单查找并使用正确的代码
• 使用术语浏览器和参考集

您可以：

• 识别并制止排斥他人的行为
• 在规划工作时考虑不同的需求