Data Scientist – Den Haag – 3 days per week on site in London - €650pd

Data Scientist with a focus on Natural Language Processing (NLP) and to contribute to innovative R&D efforts within the GenAI/NLP team. This role will focus on the application and development of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, and domain-specific GenAI solutions to support key internal use cases and products.

In this role you will:

• Design, implement and maintain scalable NLP and GenAI pipelines (including data processing, preprocessing, evaluation).
• Perform advanced data analysis on real-world datasets to extract meaningful insights and support decision-making processes.
• Stay up to date with state-of-the-art research in the space of LLMs/ NLP, proposing new ideas and methodologies that unlock business value
• Develop RAG systems and retrieval pipelines, including chunking, embedding, re-ranking, and evaluation.
• Directly contribute to experiments, including designing experimental details, writing reusable code, running evaluations, and organizing results.
• Work with a large team and help in prioritizing research that has a direct value to the products.
• Work closely with stakeholders, project managers, and architects to gather requirements, plan project scopes, and deliver projects within agreed timelines.

Requirements

We are looking for someone with:

• Deep understanding of modern NLP, LLMs, transformer architectures, prompt-engineering, RAG, agentic architectures and evaluation methodologies.
• Strong knowledge of Python programming for developing and debugging AI models.
• Excellent communication skills and a collaborative mindset with the ability to work effectively across teams and disciplines.
• Extensive experience in R&D development with an emphasis on NLP/GenAI (5+ years).
• Strong interest in cross-disciplinary collaboration to support research that delivers both business value and scientific impact.

Preferred Qualifications

• Experience in R&D development with a focus on NLP/GenAI.
• Hands-on experience building and evaluating RAG and GenAI systems in production-like settings.
• Experience in training, fine-tuning, and/or experimenting with foundation models.
• Contributions to internal or external publications or open-source projects.
• Experience supporting research coordination, such as mentoring students or collaborating with other researchers.