Data ethicist

You can:

• draw together, analyse and evaluate qualitative and quantitative data and information
• quickly read and interpret complex documents from a range of sources and distil to what is relevant
• turn research data into clear findings that inform decisions
• effectively involve colleagues in analysis and synthesis to increase consensus and challenge assumptions
• advise on the choice and application of techniques, and can critique colleagues’ findings to assure best practice
• help teams to define their project outcomes and ethical considerations, and to integrate ethical diagnostics and assessment

You can:

• demonstrate a working knowledge of social sciences (such as anthropology, economics, sociology, philosophy, psychology or race theory)
• apply various social science theories to inform data projects, products and policies, and to evaluate and challenge assumptions made in data science projects
• engage with academics and external researchers and are aware of emerging theories and concepts

You can:

• listen to the needs of technical and business stakeholders, and interpret them
• effectively manage stakeholder expectations
• manage active and reactive communication
• support or host difficult discussions within the team or with diverse senior stakeholders

You can:

• expertly translate technical concepts to non-technical audiences so they are understood by all
• demonstrate a good understanding of how technology and data products and services are built
• understand technical jargon and have sufficient knowledge to hold meaningful conversations with data science experts on issues such as minimising bias in data, or gathering, collecting, cleansing, triangulating, and reusing data
• effectively support data scientists and engineers in implementing data ethics

You can:

• incorporate a wide variety of views from underrepresented groups into product and policy work, using in-depth consulting and outreach strategies
• be involved in the wider organisational diversity and inclusion plan
• draw on your multidisciplinary background and personal experience to understand the consequences of data systems on a diverse range of stakeholders
• demonstrate a thorough understanding of social issues, types of bias and discrimination different groups can face, and you can use this knowledge to inform your data ethics work

You can:

• understand the ethical considerations of potential data science approaches
• show an awareness of the legislation applicable in this area, such as General Data Protection Regulation (GDPR) and the Data Protection Act (DPA)
• show an awareness of existing data and AI ethics frameworks in and outside government

You can:

• work with consequential or complex risks
• build consensus between services or independent stakeholders
• lead others to make good design decisions
• apply different risk methodologies in proportion to the risk

You can:

• ensure that the right actions are taken to investigate, resolve and anticipate problems
• co-ordinate the team to investigate problems, implement solutions and take preventive measures

You can:

• develop data ethics tools and translate theoretical principles into practice
• use a range of product management principles and approaches
• consider new ways of working and adapt to change
• capture and translate user needs into deliverables
• demonstrate familiarity with feedback gathering, evaluation mechanisms and product promotion

You can:

• influence stakeholders and manage relationships effectively
• build long-term strategic relationships and communicate clearly and regularly with stakeholders

You can:

• expertly draw together, analyse and evaluate qualitative and quantitative data
• quickly read and interpret complex documents from a range of sources and distil to what is relevant
• turn research data into clear findings that inform data ethics decisions for the entire organisation
• build capacity in analysis and synthesis and involve others to increase consensus and challenge assumptions
• help teams to define project outcomes and ethical considerations, and to integrate ethical diagnostics and assessment
• help an organisation continually assure and improve their practices to generate clear and valuable data ethics findings

You can:

• demonstrate expert knowledge of social sciences (such as anthropology, economics, sociology, philosophy, psychology or race theory)
• apply various social science theories to the strategic oversight of data projects, products and policies, and to evaluate and challenge assumptions made in data science projects
• demonstrate expert knowledge of existing schools of thought and best practice in data ethics
• work with academics and external researchers and you seek to publish research on applied digital ethics

You can:

• mediate between people and mend relationships, communicating with stakeholders at all levels
• manage stakeholder expectations and moderate discussions about high risk and complexity, even within constrained timescales
• speak on behalf of and represent the community to large audiences inside and outside of government

You can:

• expertly translate technical concepts to non-technical audiences so they are understood by all
• demonstrate a good understanding of how technology and data products and services are built
• understand technical jargon and have sufficient knowledge to hold meaningful conversations with data science experts on issues such as minimising bias in data, or gathering, collecting, cleansing, triangulating, and reusing data
• effectively support data scientists and engineers in implementing data ethics

You can:

• incorporate a wide variety of views from underrepresented groups into product and policy work, using in-depth consulting and outreach strategies
• be involved in the wider organisational diversity and inclusion plan
• draw on your multidisciplinary background and personal experience to understand the consequences of data systems on a diverse range of stakeholders
• demonstrate a thorough understanding of social issues, types of bias and discrimination different groups can face, and you can use this knowledge to inform your data ethics work

You can:

• expertly set and identify the ethical considerations of potential data science approaches
• demonstrate a good working knowledge of the legislation applicable in this area, such as General Data Protection Regulation (GDPR) and the Data Protection Act (DPA)
• demonstrate expert knowledge of existing data and AI ethics frameworks in and outside government and can advise others seeking ethical guidance

You can:

• work with consequential or complex risks
• build consensus between services or independent stakeholders
• lead others to make good design decisions
• apply different risk methodologies in proportion to the risk

You can:

• ensure that the right actions are taken to investigate, resolve and anticipate problems
• co-ordinate the team to investigate problems, implement solutions and take preventive measures

You can:

• define and create organisation-wide data ethics tools and translate theoretical principles into practice
• demonstrate expertise in product management principles and approaches
• set new ways of working and adapt to change
• capture and translate user needs into deliverables
• demonstrate expertise in feedback gathering, evaluation mechanisms and product promotion

You can:

• direct the strategy towards stakeholder relationships
• set stakeholder objectives and recommend that they’re met
• influence important senior stakeholders and provide mediation

Communicating between the technical and non-technical

Stakeholder relationship management

Communicating between the technical and non-technical

Managing decisions and risks

Problem management

Stakeholder relationship management

Problem management