Detailed job description and main responsibilities
In this role, you are accountable for:

Professional analytical and ethical data leadership and standards

1. Working with the Head of Data Science, Advanced Analytics & Statistics, develops and evolves a proportional organisational approach to analytical review and improvement and data ethics, ensuring processes are robust and in line with government standards, including the Aqua Book, Code of Practice for Statistics, Data Ethics Framework and relevant Government Functional Standards. This includes the development and maintenance of playbooks, standards and resources to be used across the NHSBSA.

2. Jointly responsible for the teaching/delivery of specialist training to enhance analytical and data ethics knowledge and skills of colleagues across the NHSBSA. This includes individuals and groups at all levels of the organisation.

3. Champions and raises awareness of analytical quality and data ethics issues at all levels in the organisation. Listens to, convenes, advises and facilitates difficult discussions between various parts of the organisation, while focusing on user needs.

4. Works collaboratively with a range of teams, networks and product owners across the organisation to embed principles. Including but not limited to Information Governance, Data Governance, Data Platforms, Data & Analytics Communities, Heads of Service, Inclusion Accessibility and Social Impact Lead, Statistical Publication Lead, Data Science & Advanced Analytics Lead and Open Data Lead.

5. Provides specialist advice, guidance and thought leadership across the NHSBSA on:

a. complex statistical, modelling and analytical matters to support coherence, transparency, quality, value and trustworthiness of data and statistics

b. the ethical collection, sharing and use of data throughout the organisation including the application of data science techniques, AI and generative AI to support transparency, accountability and fairness.

This includes demonstrating how to apply principles in practice and could relate to difficult and highly complex and/or contentious subject matter. It applies to individuals and groups of customers at all levels.

6. Develops frameworks for identifying, collecting, monitoring and assuring:

a. Business Critical Models (BCMs) and completing returns for DHSC. These are models/analysis where:

• The model or its outputs are used to inform essential financial and funding decisions
• Or the model is essential to achievement of business plan actions and priorities
• Or there is a high risk of damage to NHSBSA if the model is used and then subsequently found to have an error (e.g. serious reputational, financial or legal consequences)

b. Algorithm Transparency Recording Standard (ATRS) and completing returns for Central Digital and Data Office. These are algorithmic, statistical or analytical tools that either:

1. have a significant influence on a decision-making process with public effect, or
2. directly interact with the general public.

7. Undertakes reviews of important and complex analytical products including Business Critical Models to assure that analysis is fit for purpose and meets user needs. Including but not limited to assessing:
• Clarity of scope
• Appropriate data inputs, analytical methods and processes to produce high quality, realistic results
• Assumptions, risk and uncertainty are understood, managed, documented and communicated
• Appropriate outputs and communication of results to users

This includes applying expert knowledge of advanced statistical and machine learning approaches to verify and validate models/analysis and identify opportunities for improvement.

8. Undertakes reviews of data products and services, data science projects and policies to ensure that ethical considerations are embedded. Including but not limited to assessing:
• Project outcomes
• Choice and application of techniques
• Assumptions
• Potential negative consequences or sources of bias

9. Finance: The postholder contributes towards the service budget setting and headcount. Postholder will be a delegate for the service budget.

10. Communicates complex data and analyses effectively at all levels to both technical and non-technical audiences, using a range of dissemination methods. Ensures strengths and limitations are fully understood and communicated.

11. Identifies, records and mitigates organisational risks and issues associated with analytics and data ethics. Working within the NHSBSA risk management framework.

12. Jointly leads on the development of the Data & Analytics communities across the NHSBSA.

13. Contributes to the leadership of the Data Science, Advanced Analytics & Statistics service. This will include the development of the strategic direction of the service, Data and DDaT, in line with the NHSBSA Strategy. As well as promoting the value of the service within the NHSBSA and wider health and care system.

14. Keeps up to date with emerging trends, issues best practice and applicable legislation to continuously improve analytical outputs and assurance and data ethics processes.

15. Demonstrates the value of NHSBSA data and insight through networking, speaking at external events and working in the open.

16. Represents the organisation on matters relating to analytical assurance and data ethics in the NHS, DHSC, Central Digital and Data Office, Communities of Practice and wider, building lasting and strong relationships with peers across the system. This will include learning from and sharing best practice and expertise, collaboratively developing processes, polices and standards and joint working.

17. Takes responsibility for your own continuous professional development.

Person specification

Personal Qualities, Knowledge and Skills
Essential criteria

• An attitude to get things done with speed and effectiveness. The individual must be a complete self-starter and will be required to think on their feet and suggest solutions that combine multiple tools and skills sets.
• Proactive, personally motivated, self-aware, flexible and adaptable.
• Strong intellectual curiosity and ability to approach new questions, opportunities, data, and techniques with an inquisitive mind.
• Commitment to continuing professional development and keeping up to date with best practice and emerging trends analytical assurance and data ethics.
• High level of integrity, with a demonstrable commitment to upholding the highest ethical standards.
• Adopts and promotes an inclusive approach to work.
• Ability to lead, influence and build consensus at all levels in the organisation and to develop and build strong relationships with people of different business and technical backgrounds.
• Ability to apply knowledge of social issues, types of bias and discrimination different groups can face, to inform data ethics work.
• Ability to evaluate and challenge assumptions in analytics, data science and AI projects, ensuring high-quality, ethical outcomes.
• Able to critically appraise and interpret highly complex analytical projects and advise on actions based on the comparison of a range of options.
• Excellent storytelling, communication and presentation skills. With the ability to explain fundamental concepts including areas with highly complex and contentious subject matter, at all levels of the organisation with varying levels of understanding.
• Able to lead the delivery of complex, high -value projects including target setting and prioritisation of activities with the resources available.
• Strong knowledge of the Aqua Book, Code of Practice for Statistics and Government Functional Standard 010
• Strong understanding of analytical, statistical and machine learning models and validation techniques and limitations of various approaches.
• A sound understanding of the importance of data quality and analytical quality.
• Awareness of existing data and AI ethics frameworks in and outside government
• Knowledge of the ethical considerations and risks of data science, AI and Generative AI approaches.
• Strong understanding of ethical principles, including privacy, fairness, transparency, and accountability
• Awareness of the legislation applicable in this area, such as General Data Protection Regulation (GDPR), the Data Protection Act (DPA), Freedom of Information, Caldicott Principles, equality and other statutory legislation
• Good appreciation of the benefits and risks in the use of analytical, AI and Generative AI models in decision making.

• Knowledge of Business-Critical Models
• Knowledge of the Algorithm Transparency Recording Standard

• Significant experience of working collaboratively with cross-functional teams and stakeholders.
• Significant experience working in a role requiring the practical use of data science, AI and analytical skills and techniques.
• Experience of formulating work plans which cover a range of complex activities including target setting and prioritisation of activities.
• Experience of developing training materials and resources such as presentations, playbooks, standards.
• Significant experience of critically reviewing and assuring the quality of all aspects of data science and analytics project lifecycle from scoping to reporting.

• Experience undertaking analytical assurance in the public sector
• Experience building ethical controls and embedding them into broader risk management frameworks.
• Experienced in the analysis and interpretation of health or NHS related statistics.
• Experience contributing towards a Data & Analytics community.

• A first- or second-class honours degree level qualification in a numerate discipline, computer science or an equivalent subject requiring very high levels of statistical analysis. or in social sciences or humanities such as anthropology, economics, sociology, philosophy, psychology, critical race theory
• Evidence of continuous professional development.

• Master's degree or higher in a numerate discipline, computer science or an equivalent subject requiring very high levels of statistical analysis.

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