Data Scientist

Elsevier

Amsterdam

3 days ago

Amsterdam

3 days ago

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Data Scientist

This role involves designing and building machine learning, NLP, and generative AI solutions to help researchers discover knowledge faster. The position requires experience with LLMs, strong Python skills, and collaboration with cross-functional teams. The role is on-site in Amsterdam.

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On-site

Full-time

Entry Level

Machine Learning

NLP

Salary

Not specified

Work Location

Amsterdam, North Holland, Netherlands, NL

Work Model

On-site

Employment Type

Full-time

Experience Level

Not Applicable

Core Qualifications

Technical (Must-have)

machine learningNLPgenerative AIPythonPyTorchTensorFlowScikit-learnPandasNumPySciPy

Soft Skills

analytical thinkingproblem-solvingcommunicationcollaboration

Tools (Must-have)

Matplotlib

Key Responsibilities

•Design and build machine learning, NLP, and generative AI systems for scientific discovery, knowledge extraction, decision support, and intelligent content understanding.
•Work with large-scale, complex, and heterogeneous data, including scientific publications, research datasets, knowledge graphs, ontologies, taxonomies, citations, metadata, and content from every scientific discipline.
•Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI.
•Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization, question answering, and evidence-grounded generation.
•Build, evaluate, fine-tune, prompt, and integrate models into robust production systems, while continuously improving quality, relevance, reliability, and user value.
•Write clean, tested, production-quality Python and contribute reusable data science components, packages, and scalable data pipelines for preprocessing, inference, experimentation, monitoring, and continuous improvement.
•Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems.
•Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical audiences.

Data ScientistMachine LearningNLPGenerative AILLMPythonInformation ServicesFull-timeOn-siteAmsterdam

Key Responsibilities

•Design and build machine learning, NLP, and generative AI systems for scientific discovery, knowledge extraction, decision support, and intelligent content understanding.

•Work with large-scale, complex, and heterogeneous data, including scientific publications, research datasets, knowledge graphs, ontologies, taxonomies, citations, metadata, and content from every scientific discipline.

•Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI.

•Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization, question answering, and evidence-grounded generation.

•Build, evaluate, fine-tune, prompt, and integrate models into robust production systems, while continuously improving quality, relevance, reliability, and user value.

•Write clean, tested, production-quality Python and contribute reusable data science components, packages, and scalable data pipelines for preprocessing, inference, experimentation, monitoring, and continuous improvement.

•Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems.

•Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical audiences.