Data Scientist

Data Scientist (Machine Learning & MLOps) | Porto

We are looking for a freelance Data Scientist to join a newly created data unit inside a leading European group with businesses across retail, electronics, financial services, telecom and digital platforms. Python, SQL and cloud (AWS / Azure / GCP) at the core.

The challenge

The unit's mission is to bring together data from every company in the group and turn it into real products and services. You will work with datasets that most organizations simply do not have access to, and your models will feed decisions across very different business lines. This is a build phase, not a maintenance one.

️ Responsibilities

Analyze and interpret large, complex datasets to generate actionable business insights.

Build, deploy and monitor end-to-end machine learning models supporting strategic initiatives.

Design and implement feature engineering strategies.

Develop robust pipelines for model training and evaluation.

Work closely with data engineers to guarantee data reliability, and translate business needs into analytical questions.

Champion MLOps / LLMOps best practices and promote a data-first mindset across teams.

✅ Requirements

Solid experience developing, validating and deploying end-to-end Machine Learning models.

Experience in feature engineering, model tuning and ML lifecycle management.

Proficiency in Python and SQL for data manipulation and model development.

Familiarity with cloud-based data platforms (AWS, Azure, GCP).

Proven ability to translate complex business problems into actionable data solutions and communicate results clearly to diverse stakeholders.

Bachelor's or Master's degree in Mathematics, Statistics, Computer Science, Engineering or a related technical field.

Nice to have

Experience with MLOps / LLMOps tooling for scalability and performance in production.

Data visualization tools (Tableau, Power BI) and storytelling with data.

Big Data technologies (Spark, Hadoop).

Why this project

Long-term, full-time

engagement inside a newly created data unit with group-wide scope. Direct visibility with business stakeholders across multiple industries, and real ownership over the models that shape how the group uses its data.

Ready to build the data backbone of a multi-billion group? Apply and let's talk.

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