Data Discovery and Enrichment Expert

Data Discovery and Enrichment Expert Are you passionate about research and eager to work in a dynamic, international environment Do you want to ensure that cutting-edge Generative AI (GEN AI) solutions meet the highest standards of trust, quality, and reliability advancing science and education globally About our Team Our team plays a critical role in supporting GEN AI development evaluations for Elsevier s Academic and Government (AG) and Scientific, Technical and Medical Journals (STMJ) divisions. We uphold stringent quality standards for delivered content, empowering researchers, institutions, and governments to foster discovery, innovation, and societal benefit. About the Role You will primarily focus on supporting various initiatives to further develop Elsevier s products and services, within AG and STMJ. They will be related to assessing the quality of the scientific content, continuously improving the data models by providing structural feedback on the analysed data. Responsibilities Co-design and execute development evaluations for GEN AI products within Elsevier s Academic and Government (AG) division. Ensure that the evaluation processes are aligned with our Elsevier Evaluation playbook, global Responsible AI and research integrity principles. Collaborate with data scientists, product managers, and other stakeholders to ensure evaluation criteria align with product goals and Responsible AI principles. Analyze evaluation data to provide actionable insights and recommendations for model improvements. Ensure AI outputs are accurate, explainable, unbiased, and equitable. Communicate evaluation findings clearly to technical and non-technical audiences. Contribute to continuous process improvement and knowledge sharing within the team and broader organization. Mentor junior team members and support cross-functional collaboration. Requirements Master s degree in Engineering; PhD is a plus. 5+ years of experience in academic research, scientific publishing, or research technology. Experience in conducting evaluations of AI or machine learning models, preferably in academic or research-focused environments. Strong understanding of Responsible AI principles, including fairness, transparency, and accountability. Proficiency with statistical analysis, experimental design, and evaluation metrics. Excellent verbal and written communication skills, with the ability to explain complex technical concepts to diverse audiences. Detail-oriented with strong problem-solving abilities and a growth mindset. Familiarity with research lifecycle and academic publishing processes is a plus. Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.