Data Scientist

Extia; Porto; Hybrid; EUR 55,000 - 85,000; Full time

Job summary

Extia seeks an Experienced Senior Professional to join its Porto team. You will develop, train, and productionize ML models with PySpark and Databricks, while bridging technical work and business value in a hybrid environment.

You will own end-to-end MLOps, manage data pipelines, and collaborate with cross-functional teams to ensure models perform reliably in production. A strong engineering background and stakeholder communication are essential.

Qualifications

• 5+ years of hands-on experience in data science.
• Strong engineering background with a functional mindset.
• Experience designing, building, and deploying ML models.
• Deep knowledge of data pipelines and scalable data engineering.

Responsibilities

• Develop, train, and productionize ML models using PySpark and Databricks.
• Implement end-to-end MLOps with MLflow and model lifecycle management.
• Design and manage data pipelines and workflows with Airflow.
• Collaborate with cross-functional teams to translate business needs into technical solutions.

Skills

Data science

MLOps

Python

PySpark

Model deployment

Tools

Databricks

Airflow

MySQL

MLflow

GitLab

Job description

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