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Elsevier

Global STM publisher of journals.

Senior Data Scientist 1

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeAmsterdam, Netherlands€53.8k - €89.9kIn-person

About the Job

Requirements

  • A Master's or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related field.
  • At least 5 years of relevant applied data science experience focused on Generative AI, Natural Language Processing, and machine learning.
  • Proficiency in Python for data analysis, model development, and deployment.
  • Strong experience with transformer models.
  • Proficiency in Generative AI technologies, including using large language models through API access, large language model evaluation tools, and prompt engineering.
  • Knowledge of various Retrieval Augmented Generation pipelines and their practical implementation.
  • Experience building Agentic Retrieval Augmented Generation systems.
  • 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, support vector machines, logistic regression, and Bayesian modeling for model building, validation, and testing.
  • Familiarity with cloud platforms such as Bedrock, Amazon Web Services, or Azure for model deployment and production-ready pipeline creation.
  • Proficiency in data visualization tools and techniques.
  • Experience with version control systems such as GitLab or GitHub, Jira, and working in an Agile environment.
  • Proficiency in OpenSearch and Databricks.
  • Strong problem-solving and analytical skills, with attention to detail.
  • Strong communication skills and the ability to work effectively in a team-oriented environment.

Responsibilities

  • Collect and analyze data, develop models, define quality metrics, assess model quality, and regularly present findings to stakeholders.
  • Create production-ready Python packages for each data science pipeline component, such as preprocessing and model inference, and deploy them with the software engineering team.
  • Optimize and customize Retrieval Augmented Generation pipelines for project requirements involving 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 Retrieval Augmented Generation 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 data science pipeline robustness against model drift and ensure consistent output quality.
  • Establish pipeline performance reporting processes and develop automated retraining 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 small-scale projects.
  • Mentor junior data scientists and foster a knowledge-sharing culture within the team.
  • Stay up to date with advancements in artificial intelligence, machine learning, and Natural Language Processing technologies.

About the Company

Elsevier

Global STM publisher of journals.

Elsevier provides scientific, medical, and technical content and analytics to researchers, educators, clinicians, and institutions worldwide through journals, books, databases, and digital platforms. It operates by offering access to peer-reviewed articles and professional literature via online platforms, along with tools for discovery, citation tracking, research management, and clinical decision support. Unlike other publishers, Elsevier combines a broad portfolio of STM content with integrated analytics and workflow tools, serving researchers, healthcare professionals, and academic institutions on a global scale. Its goal is to enable the advancement of knowledge and improve health outcomes by delivering reliable, accessible information and data-driven solutions across the research lifecycle.

Company size
10,001+
Company stage
Not listed
Total funding
Not listed
Headquarters
Amsterdam, Netherlands
Founded
1880

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