The Young Graduate (Intern) will contribute to the continuous improvement of ESG data sourcing and reporting by refining, testing, calibrating and maintaining AI enabled solutions, with a focus on Microsoft Copilot. The role sits at the intersection of ESG data operations, process optimization, and applied AI, supporting the team in enhancing data quality, automation and reporting consistency.

This internship targets students or recent graduates interested in AI, ESG, data analytics and process automation.

Specifically, you will be required to:

1. AI Solution Support – Refinement, Testing & Calibration

· Test and validate AI prompts, workflows and Copilot based automations used for ESG data sourcing and quality checks.

· Calibrate AI outputs to ensure accuracy, consistency and alignment with predefined ESG data rules.

· Document issues, improvement opportunities and model behaviour patterns.

· Maintain prompt libraries and contribute to the continuous improvement of AI assisted procedures.

2. ESG Data Sourcing & Analysis (Operational Support)

· Identify and extract relevant ESG information from public corporate documentation.

· Validate extracted data according to ESG criteria and internal standards.

· Populate structured templates used for ESG reporting (industry type, energy consumption, emissions, natural resources, etc.).

· Escalate data quality anomalies, extraction inconsistencies and process risks.

3. Digital Process Optimization & Reporting

· Support the team in identifying opportunities to streamline ESG data workflows through AI, automation and improved templates.

· Develop and maintain basic Power BI dashboards used for activity tracking, quality indicators and process optimisation.

· Contribute to documentation updates, SOP revisions and continuous improvement initiatives.

4. Risk Awareness & Compliance

· Monitor and report potential operational risks linked to ESG data extraction or AI supported activities.

· Ensure adherence to Group Data standards, ESG governance guidelines and data quality requirements.

· Deliverables & Expected Outcomes

· Improved accuracy and consistency of AI assisted ESG data sourcing.

· Documented testing results, calibrated prompts and updated guidance.

· Enhanced reporting dashboards and ESG process documentation.

· Increased automation of repetitive tasks, contributing to operational efficiency.