Data Scientist on Azure Databricks

Project overview

Our client is looking for a Senior Data Scientist specialized in Azure Databricks and MLOps to work on technically and operationally demanding Data Science projects.

The challenge: leverage data to produce value-added analyses, develop predictive and prescriptive models, and ensure their industrialization and production monitoring.

You will work in a technological environment relying notably on Azure Databricks, MLflow, SQL, and Azure DevOps, with real responsibility for the entire model lifecycle.

Job Description

Your mission: transform data into robust, industrialized, and production-ready predictive solutions.

As a Senior Data Scientist Azure Databricks / MLOps, you will take charge of Data Science projects end-to-end, from data exploration to production deployment and model monitoring.

Responsibilities

Job Challenges

Beyond modeling, this mission requires a real ability to move from experimentation to reliable production solutions. You will need to combine technical expertise, functional understanding, and autonomy to propose relevant and sustainable solutions.

• Analyze and prepare data: explore datasets, identify relevant insights, and perform the necessary processing for their exploitation.
• Design Data Science models: develop classification, segmentation, and predictive and prescriptive analysis models.
• Manage the model lifecycle: ensure their design, training, evaluation, and production deployment on Azure Databricks.
• Industrialize models with an MLOps approach: implement best practices for deployment, monitoring, and maintenance of models in production, particularly through MLflow, Git, and Azure DevOps.
• Ensure solution performance: define KPIs, set up monitoring and alerting mechanisms, and track performance over time.
• Ensure the quality and sustainability of developments: perform unit and non-regression tests, write technical and functional documentation, and handle evolutionary and corrective maintenance.

Project details

• Start: flexible
• Remote: hybrid
• Location: Paris, France, FR
• Languages: French