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# Data Scientist

- **Company:** Royal Schiphol Group N.V.
- **Location:** SCHIPHOL, Netherlands
- **Experience:** Expert
- **Salary:** €5,703.0 - €7,912.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Governance, Data Infrastructure, Data Management
- **Published:** October 5, 2026
- **Apply:** https://www.schipholcareers.nl/vacatures/it-en-data/senior-data-scientist#apply

## About the Role

Schiphol connects your world. With the best people, we make travel safe and responsible. You contribute to this with with your unique talents, such as maintaining calm. Even when the pressure is at its highest.Also, you are the talent who shows the ability to pursue goals with enthusiasm and determination. You'll bring:

 * Fluently Dutch speaking is mandatory
 * 5+ years of experience in data science, machine learning, AI engineering or software engineering, preferably in complex enterprise environments.
 * strong programming skills in Python and experience with APIs, data pipelines and production software practices.
 * hands-on experience with LLMs, prompt engineering, retrieval-augmented generation and agentic AI frameworks such as LangGraph, Semantic Kernel, AutoGen, CrewAI or comparable tools.
 * experience with cloud and data platforms such as Azure, Databricks or similar environments.
 * understanding of MLOps, LLMOps, evaluation frameworks, observability, monitoring and model or agent governance.
 * strong stakeholder management skills and the ability to create alignment across business, technology and governance functions, being able to explain technical concepts for a non-technical audience.

## Description

* leading the design, development and deployment of agentic AI solutions that can plan, retrieve information, call tools and complete multi-step workflows.
 * translating strategic and operational challenges into clear agentic AI use cases, success criteria and delivery roadmaps.
 * designing robust agent architectures, including orchestration patterns, memory, retrieval, tool use, human-in-the-loop controls and safe fallbacks.
 * building and validating prototypes using modern AI and data platforms, then guide them towards production-grade implementation.
 * communicating the potential of AI use-cases clearly to inspire both technical and non-technical stakeholders where relevant, where AI is applicable.
 * mentoring junior colleagues and help shape standards, reusable components and best practices for agentic AI delivery.