Data Scientist / Machine Learning Engineer

About us:

At Connect Digital, we don’t just deliver digital products, we create meaningful, user-centric experiences that make a real difference. With over 20 years of market experience, we combine deep strategic thinking, world-class design, and cutting-edge tech to help organisations accelerate their digital journey. Whether it’s launching platforms, designing seamless apps, or rethinking services from the ground up, we’re all about solving complex problems with smart, elegant solutions.

If you’re curious, ambitious, and ready to help shape the next generation of digital experiences, you’ll fit right in.

About the Role

We are looking for a Data Scientist / Machine Learning Engineer to work closely with data science teams to deploy GenAI and advanced analytics models into production within a Databricks environment, operating under DevOps best practices and expanding into Azure Machine Learning for GenAI use cases.

This role covers the full development lifecycle, from experimentation to production deployment, ensuring scalable, sustainable, and high-quality solutions.

The position follows a hybrid work model in Lisbon and requires fluent English.

Key Responsibilities

• Deploy and operationalize GenAI and analytics models in production environments.
• Work within Databricks ecosystems for model training, validation, and deployment.
• Expand and support Azure Machine Learning (Azure ML) use cases.
• Contribute to the full ML lifecycle (data preparation, modeling, deployment, monitoring).
• Build and maintain data pipelines using Airflow or Databricks Pipelines.
• Implement CI/CD workflows for ML solutions (ideally using Azure DevOps).
• Collaborate in Agile/Scrum teams to ensure continuous delivery and improvement.
• Promote high-quality, scalable, and maintainable ML engineering practices.

Required Experience

• 3+ years of experience as a technical data specialist (Machine Learning Engineer, Data Engineer, or Data Scientist).
• Strong experience with Microsoft Azure.
• Hands-on experience with Databricks.
• Solid programming skills in Python (including PySpark).
• Experience with SQL and/or PySpark for data processing.
• Experience with CI/CD pipelines and version control (Git, ideally Azure DevOps).
• Experience building and orchestrating data pipelines (Airflow or Databricks Pipelines).

Technical Knowledge

Python libraries such as

• scikit-learn
• pandas
• mlflow
• Azure Machine Learning (Azure ML).
• DevOps practices applied to data/ML environments.
• Agile/Scrum methodologies (plus).

Work Model

• Hybrid – 2x a week Lisbon
• English: Fluent (mandatory)