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Senior Data Scientist – Azure Databricks Job ID JP055076

ITProposal


Job Location:

Brussels - Belgium

Monthly Salary: Not provided by the employer
Posted: 15 August 2026 (17 days ago)
Application Deadline: 12 November 2026
Vacancies: 1 Vacancy

Job Summary

Senior Data Scientist Azure Databricks
About the Role

We are looking for an experienced Senior Data Scientist to design and industrialise machine-learning solutions for large-scale healthcare data. The role combines advanced analytics technical leadership and collaboration with data engineers architects healthcare experts and business stakeholders.

Key Responsibilities
  • Develop anomaly detection risk-scoring classification and clustering models.
  • Design and industrialise ML solutions using Azure Databricks Python PySpark and SQL.
  • Build and support data/ML pipelines feature engineering and model integration.
  • Use MLflow Delta Lake Unity Catalog Databricks Workflows Azure Data Factory and Azure DevOps.
  • Define model evaluation approaches focusing on accuracy explainability and business value.
  • Apply security privacy governance and responsible-AI principles.
  • Provide technical leadership establish standards and coach team members.
Requirements
  • 10 years of experience in Data Science Machine Learning or Advanced Analytics.
  • Strong expertise in Python SQL Azure Databricks and PySpark.
  • Strong knowledge of machine-learning techniques particularly anomaly detection and risk modelling.
  • Experience with MLflow Delta Lake Unity Catalog MLOps Git CI/CD and automated testing.
  • Experience with large-scale data processing and Explainable AI.
  • Healthcare insurance fraud detection or public-sector experience is an advantage.
  • Strong analytical communication leadership and problem-solving skills.
  • Dutch or French: native/mother tongue; passive knowledge of the other national language.
  • English: professional working proficiency.
Practical Information
  • Location: Brussels Belgium
  • Work Model: Hybrid minimum 2 days onsite up to 3 days remote per week.
  • Workload: Full-time (40 hours/week)