Senior Data Scientist I

We are looking for a Senior Data Scientist I to lead the development and evaluation of advanced search and generative AI systems.

About the team

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. Elsevier supports researchers, clinicians, and life sciences professionals through trusted content, data, and analytics. Its products, including Scopus AI, LeapSpace, ClinicalKey AI, PharmaPendium, and next-generation life sciences platforms, leverage retrieval-augmented generation (RAG), semantic search, and generative AI to make knowledge more discoverable, connected, and actionable across disciplines.

About the role

This role is ideal for someone with deep hands-on experience in search, retrieval systems, RAG pipelines, and evaluation frameworks, who is ready to operate as a senior individual contributor with growing technical leadership responsibilities. 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.

Key responsibilities

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, such as LangGraph-based workflows.
• 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

• Help define and evolve evaluation strategies for search and generative AI systems across products.
• Help design robust frameworks for IR evaluation, such as NDCG, recall, and ranking quality, and GenAI evaluation, such as grounding, faithfulness, and hallucination detection.
• Contribute to development of 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, linking research and health data for more context-aware retrieval.
• Apply cutting-edge research in information retrieval, NLP, embeddings, and generative AI to continuously evolve Elsevier’s 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.

Required qualifications

• 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, including lexical, vector, and hybrid approaches.
• Experience with RAG pipelines and LLM-based systems.
• Experience with evaluation methodologies for ML, IR, and GenAI.
• Advanced programming skills in Python.
• Experience with modern ML/NLP frameworks, such as PyTorch, Hugging Face, LangChain, LangGraph, and Haystack.
• Experience working with Databricks or similar distributed data/ML platforms.
• Strong understanding of experimentation design and statistical analysis.

Preferred qualifications

• PhD in Computer Science, Data Science, Machine Learning, or a related field.
• Experience working with large-scale datasets, including scientific, biomedical, or enterprise data.
• Familiarity with scientific ontologies and metadata standards, such as MeSH, UMLS, ORCID, and CrossRef.
• Exposure to production ML systems and MLOps practices.
• Familiarity with data visualization and analytical tooling, such as Tableau, Power BI, matplotlib, seaborn, or similar, to communicate insights effectively.
• Experience with human-in-the-loop evaluation or annotation workflows.
• Publications or demonstrated applied research in IR, NLP, or generative AI.

Why join us?

Join the team and contribute to a culture of innovation, collaboration, and excellence while advancing your career and making a significant impact.

Work in a way that works for you

Elsevier promotes a healthy work/life balance and offers support through wellbeing initiatives, shared parental leave, study assistance, and sabbaticals to help employees meet immediate responsibilities and long-term goals.

• Flexible working hours to help you fit everything in and work when you are most productive.

Working for you

Benefits include:

• Dutch Share Purchase Plan
• Annual Profit Share Bonus
• Comprehensive Pension Plan
• Home, office or commuting allowance
• Generous vacation entitlement and option for sabbatical leave
• Maternity, Paternity, Adoption and Family Care leave
• Flexible working hours
• Personal Choice budget
• Variety of online training courses and career roadshows
• Wellbeing programs and gym facility in the office
• Internal communities and networks
• Various employee discounts
• Recruitment introduction reward
• Work from anywhere
• Employee Assistance Program (global)

About the business

Elsevier is a global leader in information and analytics, helping researchers and healthcare professionals advance science and improve health outcomes. The company combines quality information and vast data sets with analytics to support science and research, health education, interactive learning, healthcare, and clinical practice. Work at Elsevier contributes to major scientific and healthcare challenges through innovative technologies.