Job Title: Senior Data Scientist I
Location: UK, Netherlands
About the team:
Elsevier’s mission is to help researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics. As the landscape of science and healthcare evolves, we are pioneering intelligent discovery experiences — from Scopus AI and LeapSpace to ClinicalKey AI, PharmaPendium, and next-generation life sciences platforms. These products leverage retrieval-augmented generation (RAG), semantic search, and generative AI to make knowledge more discoverable, connected, and actionable across disciplines. 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.
About the roleWe 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.
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.
Key responsibilitiesSearch & Retrieval DevelopmentPlay 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 (e.g., 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.
Help define and evolve evaluation strategies for search and generative AI systems across products.
Help design robust frameworks for:
IR evaluation (e.g., NDCG, recall, ranking quality)
GenAI evaluation (e.g., grounding, faithfulness, 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
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.
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.
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 systemsEvaluation methodologies for ML / IR / GenAI
Advanced programming skills in Python
Experience with modern ML/NLP frameworks (e.g., PyTorch, Hugging Face, LangChain, LangGraph, Haystack)
Experience working with Databricks or similar distributed data/ML platforms
Strong understanding of experimentation design and statistical analysis
PhD in Computer Science, Data Science, Machine Learning, or a related field
Experience working with large-scale datasets (scientific, biomedical, or enterprise data)
Familiarity with scientific ontologies and metadata standards (e.g., MeSH, UMLS, ORCID, CrossRef)
Exposure to production ML systems and MLOps practices
Familiarity with data visualization and analytical tooling (e.g., 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 our team and contribute to a culture of innovation, collaboration, and excellence. If you are ready to advance your career and make a significant impact, we encourage you to apply.
Work in a way that works for you
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.
Flexible working hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
Working for you
We know that your well-being and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
- 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
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.
Primary Location Base Pay Range: NLD Amsterdam (Radarweg) €53,800 - €89,900.We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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Skills Required
- Master's or PhD in Computer Science, Data Science, Machine Learning, or 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)
- Experience with RAG pipelines and LLM-based systems
- Experience with evaluation methodologies for ML / IR / GenAI
- Advanced programming skills in Python
- Experience with modern ML/NLP frameworks (e.g., PyTorch, Hugging Face, LangChain, LangGraph, Haystack)
- Experience working with Databricks or similar distributed data/ML platforms
- Strong understanding of experimentation design and statistical analysis
- PhD in Computer Science, Data Science, Machine Learning, or related field
- Experience working with large-scale datasets (scientific, biomedical, or enterprise data)
- Familiarity with scientific ontologies and metadata standards (e.g., MeSH, UMLS, ORCID, CrossRef)
- 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
RELX Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about RELX and has not been reviewed or approved by RELX.
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Retirement Support — Retirement support is positioned as a meaningful part of total rewards through a 401(k) plan with matching contributions, alongside other financial protections such as life and disability coverage. Tuition reimbursement and share purchase access further broaden the financial value of the package beyond base salary.
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Leave & Time Off Breadth — Leave and time off breadth appears strong, with generous vacation allowances, mental health days, and options like sabbaticals and tiered PTO by tenure. Parental and caregiving leaves are described in detail, reinforcing time-away benefits as a standout component of the overall package.
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Wellbeing & Lifestyle Benefits — Wellbeing and lifestyle benefits are supported by offerings such as mental health support (e.g., app access), EAP resources, gym-related perks, and wellness incentives. Flexible working hours and related work-life supports add to the perceived day-to-day value of benefits.
RELX Insights
What We Do
RELX is a global provider of information-based analytics for professional and business customers across industries. We help scientists make new discoveries, doctors and nurses improve the lives of patients and lawyers win cases. We prevent online fraud and money laundering, and help insurance companies evaluate and predict risk. Our events enable customers to learn about markets, source products and complete transactions. In short, we enable our customers to make better decisions, get better results and be more productive. We do this by leveraging a deep understanding of our customers to create innovative solutions which combine content and data with analytics and technology in global platforms. RELX serves customers in more than 180 countries and has offices in about 40 countries. It employs approximately 30,000 people of whom almost half are in North America. We operate in four major market segments: Scientific, Technical & Medical; Risk & Business Analytics; Legal; and Exhibitions.





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