Data Scientist

You want to join a company that places people at the heart of its concerns? We are waiting for you at Extia!

As a consulting company specialized in IT and digital sectors, Extia has prioritized an approach that combines performance and well-being at work since its creation in 2007. This vision is shared today by more than 2,500 Extians across France and internationally, and has been recognized by the Great Place to Work® certification for 15 years!

We believe in equal opportunity and offer every candidate the chance to reveal their potential, without distinction of any kind. At Extia, it's "First who, then what" so, let's do it!

Experienced Senior Professional: You bring 5+ years of hands-on experience in data science, with a proven track record of designing, building, and deploying machine learning models.

Hybrid Mindset (Technical + Functional): You have a strong engineering background with deep technical rigor, but you also possess a functional mindset. You understand the business context, communicate effectively with stakeholders, and bridge the gap between technical complexity and business value.

MLOps & Engineering Native: You care deeply about clean code, continuous integration, model lifecycle management, and scalable data engineering.

Develop & Train Models: Build, optimize, and scale machine learning models to solve complex business problems using PySpark and Databricks.

• End-to-End MLOps & Productionization: **Utilize MLflow to track, log, and register models, taking full ownership of moving models from experimentation into robust production environments.
• Workflow Automation & Orchestration: **Design and manage data pipelines and model workflows using Airflow.

Database & Version Control Management: Query and interact with relational databases (MySQL) and maintain code standards, CI/CD pipelines, and version control using GitLab.

Collaborate & Drive Functional Impact: Work closely with cross-functional teams to translate business requirements into technical solutions and ensure models perform reliably in production.

_Key Technical Stack Required:

_Languages & Frameworks: PySpark, Python, Machine Learning models

Data & Orchestration Tools: Databricks, Airflow, MySQL

MLOps & DevOps: MLflow (Model registry & production deployment), GitLab, CI/CD