Senior Data Scientist

RELX

Senior Data Scientist developing cutting-edge Gen AI models for Elsevier's life science products. Collaborating with developers and subject matter experts to optimize data science solutions.

Posted 7/8/2026full-timeAmsterdam • 🇳🇱 NetherlandsSenior💰 €53,800 - €89,900 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying Generative AI models, with a strong focus on Python programming, data science project lifecycle management, and collaboration with cross-functional teams. Proficient in building and optimizing Retrieval Augmented Generation (RAG) systems and ensuring high-quality outputs through rigorous testing and evaluation.

Highest-signal resume keywords

Generative AI TechnologiesPython ProgrammingRAG Pipeline ImplementationTransformer ModelsData Science Project Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonGenerative AINLPMachine LearningDeep LearningReinforcement LearningData AnalysisModel DevelopmentData VisualizationQuality Assessment

Soft Skills

Problem-SolvingAnalytical SkillsAttention to DetailCommunication SkillsTeam Collaboration

Tools & Technologies

LangChainOpenSearchDatabricksAWSAzureGitLabGitHubJira

Certifications & Qualifications

Master’s or Ph.D. in Computer ScienceData ScienceArtificial Intelligence

Industry Keywords

Data ScienceGenerative AINLPRAG SystemsAI Agent Management

Tech Stack

Tools & technologies

AWSAzureCloudPython

About the role

Key responsibilities & impact

Play a pivotal role in the development and deployment of cutting-edge Gen AI models and solutions
Responsible for building, testing, and maintaining our Gen AI, RAG and NLP solutions
Work throughout the whole life cycle of data science projects: design, implementation, production and beyond
Deliver efficient and production-ready Python code
Collaborate closely with developers to deploy and productionize our data science pipelines
Collaborate with subject matter experts in biology and chemistry domains to validate the output
Data collection, data analysis, model development, defining quality metrics, quality assessment of models and regular presentations to stakeholders
Create production-ready Python packages for each component of data science pipelines (such as pre-processing and model inference) and their deployment together with software engineering team
Optimize and customize Retrieval Augmented Generation (RAG) pipelines to meet specific project requirements that involve content ingestion, machine translation, and contextualized information retrieval
Ingest, preprocess, and transform large-scale multilingual data to ensure high-quality inputs for downstream models
Build AI agentic models integrated with RAG pipelines
Conduct rigorous testing and evaluation of AI models to ensure high performance and reliability
Integrate data science components and perform end-to-end quality assessments
Maintain robustness of data science pipelines against model drift and ensuring consistent output quality
Establish reporting processes for pipeline performance and develop automated re-training strategies for existing pipelines
Collaborate with cross-functional teams to integrate AI solutions into existing products and services
Lead and manage projects with a team of data scientists and independently execute the entire small-scale projects
Mentor junior data scientists and foster a knowledge-sharing culture within the team
Stay up-to-date with the latest advancements in AI, machine learning, and NLP technologies.

Requirements

What you’ll need

Master’s or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related field
5+ years of relevant applied experience in data science, with a focus on Generative AI, NLP, and machine learning
Proficiency in Python for data analysis, model development, and deployment
Strong experience with transformer models
Proficiency in Generative AI technologies, including utilizing LLMs via API access, LLM evaluation tools, and prompt engineering
Knowledge of various RAG pipelines and their practical implementation
Experience building Agentic RAG systems is strong requirement
Experience with AI agent management frameworks such as LangChain, or similar tools
Experience with advanced algorithms in deep learning, neural networks, reinforcement learning, and transfer learning
Familiarity with traditional machine learning algorithms such as random forests, SVM, logistic regression, and Bayesian modelling for model building, validation, and testing
Familiarity with cloud platforms (e.g., Bedrock, AWS, Azure) for model deployment and the creation of production-ready pipelines
Proficiency in data visualization tools and techniques
Experience with version control systems (e.g., GitLab or GitHub), Jira, and working in an Agile environment
Proficient in using OpenSearch and Databricks
Excellent problem-solving and analytical skills, with strong attention to detail
Strong communication skills and the ability to work effectively in a team-oriented environment.

Benefits

Comp & perks

Flexible working hours
Wellbeing initiatives
Shared parental leave
Study assistance
Sabbaticals