数据科学主管

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:

• work with data engineers and data scientists to design and provide products for the organisation

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:

• demonstrate practical knowledge of data science tools and techniques
• develop data science solutions that maximise insight
• identify opportunities for how data science can improve data practices

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 and test scripts and create basic models in one or more languages
• collaborate on shared codebases, using a variety of methodologies

You can:

• understand the differences between delivery methods, such as Agile and waterfall, and can choose the most appropriate method to deliver each product
• define the minimum viable product (MVP) and support decisions about priorities
• work with specialists in multidisciplinary teams to smoothly deliver data science products into the organisation

您可以：

• 凭借对医疗卫生和照护体系的深刻理解塑造组织战略
• 代表组织与医疗卫生和照护领域的合作伙伴及负责人沟通
• 预判政策和服务变化将如何影响数字服务和照护

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：

• 制定组织在照护中保证和监测人工智能的标准
• 领导高风险模型在部署前后的保证工作
• 在安全公平的人工智能方面代表组织与监管机构和合作伙伴沟通

您可以：

• 领导产品或变更的危害识别和风险评估
• 编写和维护危害日志及临床安全案例报告
• 与产品团队商定风险控制措施并检查其有效性
• 就如何应用临床风险管理标准向团队提供建议

您可以：

• 评估某个产品是否属于医疗器械及其可能的类别
• 与质量和临床同事一起规划产品的监管工作

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

您可以：

• 持有并管理预算，进行预测并解释差异
• 编制包含成本和效益的商业论证