Teams at Elsevier

Define and lead AI and data science strategy across ML, NLP, search, recommendation, experimentation, and generative AI. Lead and develop teams to deliver production-ready AI systems (LLMs, RAG, semantic search, embeddings), establish evaluation and responsible AI frameworks, and influence cross-functional stakeholders to align roadmaps and drive measurable product and business outcomes.

Design and build ML, NLP, and generative AI systems for scientific discovery and knowledge extraction. Work with large heterogeneous scientific datasets to develop semantic search, entity extraction, QA, summarization, embeddings, and production-ready models. Implement model evaluation, fine-tuning, deployment, monitoring, drift detection, and scalable data pipelines while collaborating across engineering, product, UX, and research teams.

Design and deliver production-ready AI, NLP, and generative-AI solutions (including LLMs and RAG) for knowledge discovery. Build retrieval, ranking, recommendation, and decision-support systems, integrate scientific metadata and ontologies, establish evaluation and monitoring, write production Python code, and provide technical leadership and mentoring.