首席数据科学家

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

您可以：

• 分析一项服务如何融入跨组织的照护路径
• 与临床医生、照护人员和患者合作塑造数字服务
• 解释数字决策对照护、安全和员工工作量的影响

您可以：

• 领导数据保护影响评估和信息共享协议
• 就合法依据、同意、保密和保存向团队提供建议
• 调查事件并提出改进建议

您可以：

• 设计将标识符与分析数据分开保存的假名化和关联方法
• 评估数据集或出版物的再识别风险，并选择合适的控制措施
• 就可信研究环境等安全环境向团队提供建议

您可以：

• 与临床同事一起规划模型的验证、偏差评估和上线后监测
• 判断模型何时需要重新训练、限制使用或撤回
• 就模型何时可能作为医疗器械受到监管以及需要哪些证据向团队提供建议

您可以：

• 参加危害研讨会并为危害日志作出贡献
• 在您的工作中遵循临床风险管理流程
• 为临床安全案例提供证据，例如测试结果

您可以：

• 遵循符合医疗器械标准的软件生命周期流程
• 编制此类流程所要求的记录

您可以：

• 直线管理一个团队，设定目标并开展考评
• 关注身心健康，管理出勤、绩效和行为
• 规划团队的发展和继任