Data and AI Governance Analyst Trainee/Intern

Purpose of the role

To gain experience of risk management skills, knowledge, and capabilities to deliver a broad range of compliance services to businesses and functions.

Accountabilities

• Guiding the business’ adherence to the Compliance risk management framework.
• Advisory services to colleagues about regulation related to specific products and services.
• Utilisation of data and analytics to proactively monitor and influence the business Compliance risk landscape.
• Development of Compliance risk insight and understanding, including Laws, Rules and Regulations, Financial Crime and Conduct.
• Training of business stakeholders.

Analyst Expectations

• To meet the needs of stakeholders/ customers through specialist advice and support
• Perform prescribed activities in a timely manner and to a high standard which will impact both the role itself and surrounding roles.
• Likely to have responsibility for specific processes within a team
• They may lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources. They supervise a team, allocate work requirements and coordinate team resources.
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
• OR for an individual contributor, they manage own workload, take responsibility for the implementation of systems and processes within own work area and participate on projects broader than direct team.
• Execute work requirements as identified in processes and procedures, collaborating with and impacting on the work of closely related teams.
• Check work of colleagues within team to meet internal and stakeholder requirements.
• Provide specialist advice and support pertaining to own work area.
• Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct.
• Maintain and continually build an understanding of how all teams in area contribute to the objectives of the broader sub-function, delivering impact on the work of collaborating teams.
• Continually develop awareness of the underlying principles and concepts on which the work within the area of responsibility is based, building upon administrative / operational expertise.
• Make judgements based on practise and previous experience.
• Assess the validity and applicability of previous or similar experiences and evaluate options under circumstances that are not covered by procedures.
• Communicate sensitive or difficult information to customers in areas related specifically to customer advice or day to day administrative requirements.
• Build relationships with stakeholders/ customers to identify and address their needs.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.

Purpose of the Role:
The Data & AI Governance Analyst plays a critical role in driving data-led decision-making, strengthening regulatory compliance, and enabling the responsible adoption of Artificial Intelligence (AI) across the organization. The role uses advanced analytics, statistical techniques, business intelligence, and AI-enabled solutions to identify emerging risks, improve customer outcomes, enhance control effectiveness, and support strategic business objectives.
Operating at the intersection of Compliance, Risk, Technology, and Business, the individual will transform complex data, regulatory requirements, and business challenges into actionable insights, scalable monitoring solutions, and robust governance frameworks. The role will help ensure that AI and analytics solutions are deployed in a controlled, transparent, ethical, and well-governed manner throughout their lifecycle.
By combining analytical expertise with AI understanding and governance principles, the role will support early risk detection, evidence-based decision-making, operational efficiency, and sustainable innovation, while maintaining strong regulatory compliance, customer protection, and Responsible AI standards.

Key Accountabilities:

• Deliver advanced analytics, exploratory data analysis (EDA), and statistical analysis to identify emerging risks, customer harms, trends, and opportunities across large and complex datasets.
• Translate business and regulatory requirements into data-driven solutions that support compliance, risk management, and strategic decision-making.
• Generate actionable insights and recommendations that improve customer outcomes, strengthen controls, and enable proactive risk mitigation.
• Use AI, natural language processing (NLP), automation, and advanced analytics to improve analytical efficiency, monitoring capability, and insight generation.
• Support the responsible adoption of AI by ensuring solutions align with regulatory, ethical, governance, and internal control requirements.
• Assess and monitor AI-related risks across the lifecycle, including model performance, governance, transparency, explainability, accountability, human oversight, and control effectiveness.
• Develop and maintain dashboards, management information (MI), and key risk indicators (KRIs) to support effective risk and compliance oversight.
• Partner with Compliance, Risk, Technology, and Business stakeholders to solve complex challenges and drive data-led decision-making.
• Produce high-quality executive reports and presentations that communicate complex analytical and AI-related insights clearly to senior leadership and governance forums.
• Drive continuous improvement and innovation through the adoption of data, automation, AI, and industry best practices while maintaining strong governance and regulatory compliance.

Role Expectations:

A successful candidate will be able to:

• Independently perform EDA and descriptive statistical analysis to derive meaningful business and risk insights.
• Translate business and regulatory requirements into structured analytical approaches and data-driven solutions.
• Identify trends, anomalies, emerging risks, and customer outcome concerns from large and complex datasets.
• Develop dashboards, visualizations, and MI that support effective decision-making and risk monitoring.
• Apply Python, SQL, and analytical tools to extract, transform, analyze, and interpret data.
• Demonstrate practical understanding of AI, Generative AI, and AI-enabled analytics, including their opportunities, limitations, and risks.
• Apply key AI governance and Responsible AI principles, including fairness, transparency, explainability, accountability, and human oversight.
• Communicate findings clearly and confidently to technical and non-technical stakeholders through reports and presentations.
• Generate evidence-based recommendations that improve customer outcomes, compliance, and risk management.
• Demonstrate ownership, curiosity, problem-solving ability, stakeholder engagement, and delivery of high-quality work with minimal supervision.

Business & Communication Skills

• Stakeholder Management: Engage stakeholders, understand business and regulatory requirements, manage expectations, and influence decisions through data-driven insights.
• Communication: Explain complex analytical, statistical, and AI-related concepts clearly and concisely to technical and non-technical audiences.
• Executive Reporting: Synthesize large volumes of data into actionable insights, MI, and concise, management-ready presentations.
• Business Partnering: Collaborate across Compliance, Risk, Technology, and Business to translate challenges into analytical solutions and measurable outcomes.
• Data Storytelling: Present findings, trends, risks, and opportunities through compelling narratives that support strategic decisions and business impact.

Qualifications:

• Currently pursuing an undergraduate degree in Computer Science, Data Science, Artificial Intelligence, Information Systems, or a related discipline.
• Strong interest in Artificial Intelligence, machine learning, technology risk, and governance.
• Analytical and problem-solving skills with the ability to evaluate complex issues.
• Strong written and verbal communication skills.
• Coursework or project experience involving machine learning, AI systems, model development, or AI governance.
• Familiarity with AI lifecycle concepts, model risk management, data governance, or technology risk frameworks.
• Experience with data analytics tools such as Python, SQL, Power BI, or similar technologies.
• Understanding regulatory, compliance, or risk management concepts is an advantage.