Senior Data Scientist - Real-Time ML for Aviation Ops

Xebia Group; Amsterdam; Hybrid; EUR 75,000 - 110,000; Full time

Benefits offered by this job

Good salary

25 vacation days

Technical trainings & Innovation days

Macbook and Iphone

Lunches and coffee bar

Flexibility in working from home & at

Job summary

Xccelerated in Amsterdam is seeking a Senior Data Scientist to join the Data team that blends data science with ML engineering. You’ll turn data into production-ready models and tools that help crews and planners make faster, better decisions in aviation.

You’ll work on extracting insights from diverse data sources, building and productionizing AI/ML models, and contributing to large-scale optimization projects. The role emphasizes deploying models in live environments and ongoing monitoring.

Qualifications

• 4–6 years of work experience as a Data Scientist or ML professional.
• Hands-on experience with both data science and ML deployment into production.
• Knowledge of open-source tech like Spark, Kafka, Airflow or Kubernetes.

Responsibilities

• Extract insights from fast-growing operational and flight data sources.
• Build and productionize AI/ML models that predict flight delays, optimize maintenance planning, and support smarter crew scheduling.
• Contribute to large-scale optimization and simulation projects.
• Develop tools that make complex processes transparent for planners and crews, enabling faster decision-making.
• Work with real-time data and robust calculations to improve passenger and crew experience.

Skills

Data science

Machine learning

Spark

Kafka

Airflow

Kubernetes

Tools

Spark

Kafka

Airflow

Kubernetes

Job description

Xccelerated in Amsterdam is seeking a Senior Data Scientist to join the Data team that blends data science with ML engineering. You’ll turn data into production-ready models and tools that help crews and planners make faster, better decisions in aviation.

You’ll work on extracting insights from diverse data sources, building and productionizing AI/ML models, and contributing to large-scale optimization projects. The role emphasizes deploying models in live environments and ongoing monitoring.