Data Discovery and Enrichment Expert II

# Data Discovery and Enrichment Expert II

Are you passionate about research and keen to develop your skills in a dynamic, international environment? Do you want to contribute to ensuring that innovative Generative AI (GEN AI) solutions meet high standards of trust, quality and reliability?

## About the Team

Our team plays a key role in supporting GEN AI development evaluations for Elsevier's Academic and Government (A&G) division. We maintain rigorous quality standards for delivered content and enable researchers, institutions and governments to advance discovery and innovation.

## About the Role

You will support LeapSpace, a leading product that provides researchers with intelligent, contextual and personalised support throughout their research lifecycle—from ideation and fundraising to planning, analysis and writing. This project is central to Elsevier's vision of transforming research workflows with AI.

## Responsibilities

• Assist in designing and executing development evaluations for GEN AI products within Elsevier's A&G division
• Help ensure that evaluation processes align with Elsevier's Evaluation Playbook and Responsible AI principles
• Collaborate with data scientists, product managers and other stakeholders to support evaluation criteria and data collection
• Analyse evaluation data and contribute to actionable insights and recommendations
• Support efforts to ensure that AI outputs are accurate, explainable, unbiased and fair
• Communicate evaluation results clearly to technical and non-technical audiences
• Contribute to continuous process improvements and knowledge sharing within the team
• Learn from and collaborate with senior team members and cross-functional teams

## Requirements

• Bachelor's degree in engineering
• Some experience or internships in data analysis, AI/ML evaluation or related fields is a plus
• Basic knowledge of Responsible AI principles such as fairness, transparency and accountability
• Familiarity with statistical analysis, experimental design and evaluation metrics is desirable
• Strong desire to learn and develop technical and collaboration skills
• Good communication skills and ability to work effectively in teams
• Detail-oriented with a problem-solving mindset
• Interest in academic research lifecycle and publishing is a bonus