Xccelerated | Part of Xebia

ML engineer in aviation

In short

Senior Data Scientist / ML Engineer role in the aviation industry, building and productionizing AI/ML models for flight delay prediction, maintenance planning, and crew scheduling. The team works at the intersection of Data Science and ML Engineering, handling real-time operational and flight data, optimization/simulation projects, and GenAI/LLM implementations. Requires 4-6 years of experience as a Data Scientist or ML(OPS), hands-on production ML skills, and knowledge of Spark, Kafka, Airflow, Kubernetes, and GenAI/RAG pipelines. Hybrid role based in Amsterdam.

About the Role
We're looking for a Senior Data Scientist to join our growing Data team working at the intersection of Data Science and Machine Learning Engineering. As part of this team, you'll turn data into tools and models that help crews and planners make better, faster decisions and build sustainable solutions for the aviation of the future.
Responsibilities
•Extracting insights from fast-growing operational and flight data sources
•Building and productionizing AI/ML models that predict flight delays, optimize maintenance planning, and support smarter crew scheduling
•Contributing to large-scale optimization and simulation projects
•Developing tools that make complex operational processes more transparent for planners and crews, supporting faster decision-making
•Working with real-time data and smart calculations to improve the passenger and crew experience
Requirements
•Customer focused with a strong can-do mentality
•Results-focused, with a desire to complete challenging tasks and learn while doing
•A background in Data Science, Business Analytics, or Artificial Intelligence
•4-6 years of work experience as a Data Scientist or ML(OPS)
•Hands-on experience with both the Data Science side (modeling, analysis) and the Machine Learning side, including getting models into production
•Knowledge of open-source technologies like Spark, Kafka, Airflow or Kubernetes
•Demonstrated experience with production-grade GenAI implementations (modern GenAI/LLM frameworks such as RAG pipelines)
•Active stakeholder interaction
Conditions
•Good salary
•25 vacation days
•Technical trainings & Innovation days for a full year (every week)
•Challenging assignment
•Macbook and iPhone
•Lunches, amazing coffee and snack bar
•Flexibility in working from home & at the office in Amsterdam

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