Senior Machine Learning Data Scientist - Azure Databricks (Freelance possible)

EngiFlex; Brussel Hoofdstad; Sur place; EUR 90 000 - 120 000; Plein temps

Avantages offerts par ce poste

Company car

Budget for extra education/certif.

Career plan

Résumé du poste

EngiFlex invites a senior data science leader to join a multidisciplinary team in Belgium, focusing on advanced anomaly-detection within healthcare data. You will design and industrialise scalable ML solutions on Azure Databricks, leveraging PySpark, MLflow and Delta Lake.

You will guide architecture, collaborate with domain experts and engineers, and ensure governance, security and explainability across the project lifecycle.

Qualifications

• Master's or PhD in data-related field or equivalent practical experience.
• 10+ years of experience in data science, machine learning or advanced analytics.
• Strong Python, SQL, Azure Databricks and PySpark skills.
• Deep knowledge of anomaly detection, classification and clustering.
• Experience with MLflow, Delta Lake, Unity Catalog, Databricks Workflows and MLOps.
• Healthcare, insurance, fraud detection or public sector experience is a strong asset.
• Comfortable in an agile environment; strong communication and leadership.

Responsabilités

• Lead the design, development and industrialisation of machine-learning solutions in Azure Databricks.
• Work closely with domain experts, data engineers, business analysts and other stakeholders to identify valuable use cases and translate business needs into analytical solutions.
• Build anomaly-detection, risk-scoring and classification models using supervised and unsupervised machine-learning techniques.
• Define model evaluation methods covering performance, explainability and operational impact.
• Contribute to data and ML pipelines, feature engineering and integration of solutions into the wider platform.
• Use Databricks and Azure services such as PySpark, Delta Lake, Unity Catalog, MLflow, Workflows, Azure Data Factory, Azure DevOps and Azure Storage.
• Apply security, privacy, governance and responsible-AI requirements throughout the solution lifecycle.
• Provide technical leadership, help define standards and coach other team members.

Connaissances

Python

SQL

Azure Databricks

PySpark

MLflow

Delta Lake

Unity Catalog

Databricks Workflows

MLOps

Git

CI/CD

Explainable AI

Risk modelling

Formation

Master's degree or PhD in Data Science/CS/AI/Statistics/Engineering

Outils

Azure DevOps

Azure Data Factory

Delta Lake

MLflow

Description du poste

Tasks and responsibilities

You will join a multidisciplinary data and AI environment with data scientists, data engineers, architects, analysts, project managers and domain experts. In this role, you contribute to the development of advanced anomaly-detection solutions that analyse large volumes of Belgian healthcare data, detect unusual billing patterns, prioritise high-risk cases and support medical and administrative controls with explainable, data-driven insights.

The work focuses on designing and industrialising scalable machine-learning solutions within the Microsoft Azure ecosystem, with Azure Databricks as a core platform.

Responsibilities

• Lead the design, development and industrialisation of machine-learning solutions in Azure Databricks.
• Work closely with domain experts, data engineers, business analysts and other stakeholders to identify valuable use cases and translate business needs into analytical solutions.
• Build anomaly-detection, risk-scoring and classification models using supervised and unsupervised machine-learning techniques.
• Define model evaluation methods covering performance, explainability and operational impact.
• Contribute to data and ML pipelines, feature engineering and integration of solutions into the wider platform.
• Use Databricks and Azure services such as PySpark, Delta Lake, Unity Catalog, MLflow, Workflows, Azure Data Factory, Azure DevOps and Azure Storage.
• Apply security, privacy, governance and responsible-AI requirements throughout the solution lifecycle.
• Provide technical leadership, help define standards and coach other team members.

Your profile

• Master's or Ph.D. in Data Science, Computer Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or equivalent practical experience.
• Minimum 10 years of experience in data science, machine learning or advanced analytics.
• Strong hands-on experience with Python, SQL, Azure Databricks and PySpark.
• Deep knowledge of machine-learning techniques, including anomaly detection, classification and clustering.
• Experience with MLflow, Delta Lake, Unity Catalog, Databricks Workflows and MLOps practices.
• Experience with Git, automated testing and CI/CD.
• Background in explainable AI, risk modelling, risk scoring and large-scale data processing.
• Experience in healthcare, insurance, fraud detection or the public sector is a strong asset.
• Comfortable working in an agile environment.
• Strong analytical and technical capabilities, combined with a pragmatic and autonomous approach.
• Delivery-focused, with a strong sense of ownership and problem-solving ability.
• Able to turn business needs into scalable analytical solutions.
• Clear communicator with leadership skills and a strong focus on explainability, quality and maintainability.
• Collaborative, flexible and eager to keep learning.
• Dutch or French at mother-tongue level, with passive knowledge of the other national language.
• Professional working proficiency in English.

Summary

This role combines advanced analytics, machine learning and technical leadership. You will help develop and industrialise scalable solutions using Azure Databricks, Python, PySpark, MLflow and Azure services in a data-rich healthcare context.

Offer

You will be part of a growing Belgian SME where initiative and personal development are encouraged. We will provide you with an enjoyable work environment with fun colleagues. We will work out a career plan with you, with attention and a budget for extra education/certification. You can count on an attractive salary, supplemented with extra-legal benefits, including a company car.
(Freelance is also possible)