Senior Data Scientist

Job Title:

Senior Data Scientist I

Location:

UK, Netherlands

Elsevier’s mission is to help researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics. The Search & AI Evaluation team sits within the Platform Data Science organization and is responsible for advancing enterprise‑scale search, retrieval, and evaluation capabilities across Elsevier's global products.

We are looking for a Senior Data Scientist I to lead the development and evaluation of advanced search and generative AI systems. You will own complex problem areas end‑to‑end, drive methodological rigor in evaluation, and contribute to the technical direction of retrieval and RAG systems.

• Search & Retrieval Development
  • Play a leading role in the design and optimization of lexical, vector, and hybrid retrieval systems at scale.
  • Help architect and improve RAG pipelines, including retrieval strategies, prompt design, and system orchestration.
  • Help drive experimentation with embeddings, re‑ranking models, and retrieval architectures to significantly improve relevance and user outcomes.
  • Partner with engineering to ensure robust, scalable, and production‑ready implementations.
• Evaluation & Experimentation
  • Define and evolve evaluation strategies for search and generative AI systems across products.
  • Design robust frameworks for IR evaluation, GenAI evaluation, and develop evaluation datasets, gold standards, and annotation strategies.
  • Guide and review experimental design, including offline evaluation and A/B testing, ensuring statistical rigor and validity.
  • Contribute to responsible AI practices, including bias, fairness, and risk evaluation.
• Generative AI & Applied Research
  • Apply and adapt state‑of‑the‑art techniques in NLP, embeddings, and generative AI to production use cases.
  • Evaluate and integrate emerging technologies into the team’s roadmap.
  • Contribute to knowledge graph and semantic enrichment efforts that support retrieval systems.
• Domain & Research Integration
  • Collaborate with domain experts, ontology engineers, and biomedical informaticians to integrate scientific taxonomies, citation networks, and clinical ontologies into retrieval systems.
  • Incorporate structured data—including datasets, chemical entities, genes, drugs, clinical trials, and patient outcomes—into AI‑powered discovery pipelines.
  • Advance Elsevier’s knowledge graph and metadata integration strategy.
  • Apply cutting‑edge research in information retrieval, NLP, embeddings, and generative AI to continuously evolve the discovery and evaluation stack.
• Collaboration & Delivery
  • Work closely with product, engineering, and domain experts to define and deliver impactful solutions.
  • Communicate findings and recommendations clearly to both technical and non‑technical stakeholders.
  • Take ownership of projects from problem definition through experimentation and deployment.

• Master’s or PhD in Computer Science, Data Science, Machine Learning, or a related field (or equivalent practical experience).
• ~3–5+ years of experience in data science, machine learning, or applied NLP.
• Strong hands‑on experience with
  • Search and retrieval systems (lexical, vector, hybrid).
  • RAG pipelines and LLM‑based systems.
  • Evaluation methodologies for ML / IR / GenAI.
  • Advanced programming skills in Python.
  • Modern ML/NLP frameworks (PyTorch, Hugging Face, Lang Chain, Lang Graph, Haystack).
  • Distributed data/ML platforms such as Databricks.
  • Experimentation design and statistical analysis.

• PhD in Computer Science, Data Science, Machine Learning, or a related field.
• Experience with large‑scale scientific, biomedical, or enterprise datasets.
• Familiarity with scientific ontologies and metadata standards (e.g., MeSH, UMLS, ORCID, Cross Ref).
• Exposure to production ML systems and MLOps practices.
• Familiarity with data visualization and analytical tooling (e.g., Tableau, Power
  
  BI, matplotlib, seaborn).
• Experience with human‑in‑the‑loop evaluation or annotation workflows.
• Publications or demonstrated applied research in IR, NLP, or generative AI.

• Dutch Share Purchase Plan
• Ann…