Senior Data Scientist I

This role sits within Elsevier's Platform Data Science organization, a centralized AI and data science group responsible for advancing intelligent discovery, retrieval, and generative AI capabilities across Elsevier products and platforms. The organization develops foundational AI technologies that power experiences such as LeapSpace, Elsevier's AI-powered research assistant, as well as Elsevier's broader Search & AI Platform.

• Search and retrieval systems
• Generative AI and LLM applications
• AI evaluation and experimentation
• Semantic enrichment and knowledge systems
• Scalable AI platforms and intelligent workflows

We are looking for a Senior Data Scientist I to help design, build, and evaluate advanced AI capabilities powering LeapSpace. This role will focus heavily on applied AI research and development, including prototyping intelligent workflows, integrating large language models with trusted scientific data, and advancing AI-assisted research experiences.

• Lead prototyping and development of LLM-powered research workflows, including:
• Scientific question answering
• Literature summarization
• Semantic exploration and discovery
• Research insight generation
• Citation-aware reasoning workflows
• Design and iterate on agentic and multi-step AI workflows using frameworks such as LangGraph and related orchestration tooling.
• Apply state-of-the-art techniques in:
• NLP
• Generative AI
• Embeddings and semantic representations
• Retrieval-augmented generation (RAG)
• AI reasoning and orchestration
• Rapidly evaluate emerging AI models, tooling, and frameworks to identify opportunities for product innovation.
• Translate applied AI research into scalable, production-oriented solutions that improve researcher productivity and trust.
• Contribute to experimentation around prompt engineering, context management, grounding strategies, and hallucination mitigation.
• Support integration of scientific metadata, ontologies, and knowledge assets into AI workflows.
• Design and optimize search and retrieval pipelines, including lexical, vector, and hybrid retrieval approaches.
• Develop and improve RAG systems that integrate LLMs with trusted scientific and biomedical content.
• Experiment with embeddings, re-ranking models, chunking strategies, and retrieval orchestration to improve relevance and answer quality.
• Build scalable workflows for semantic search and knowledge discovery.
• Collaborate closely with engineering teams to productionize AI and retrieval systems.

Qualifications:

• Master's or PhD in Computer Science, Data Science, Machine Learning, NLP, Information Retrieval, or a related field
• ~3-5+ years of experience in applied AI, machine learning, NLP, or information retrieval
• Strong hands-on experience with:
• LLM-based applications and generative AI systems
• RAG pipelines and retrieval systems
• Search and retrieval architectures (lexical, vector, hybrid)
• Evaluation methodologies for IR and generative AI systems
• Advanced programming skills in Python
• Experience with modern AI/ML frameworks and tooling (e.g., PyTorch, Hugging Face, LangChain, LangGraph, Haystack)
• Experience working with Databricks or similar distributed data/ML platforms
• Strong understanding of experimentation design, evaluation frameworks, and statistical analysis
• Proficiency with data visualization and analytical tooling (e.g., Tableau, Power BI, matplotlib, seaborn)
• Experience building AI assistants, agentic workflows, or conversational AI systems
• Experience working on large-scale search, ranking, or recommendation systems
• Familiarity with scientific, biomedical, or scholarly datasets
• Experience with knowledge graphs, ontologies, or semantic enrichment systems
• Exposure to production ML systems and MLOps practices
• Publications or applied research contributions in NLP, IR, search, or generative AI
• Experience building AI systems in regulated, high-trust, or content-rich domains

We promote a healthy work/life balance across the organization. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. As a global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits.