.EU Data Scientist - Machine Learning & Decision IntelligenceHybrid - Lisbon, Portugal - €60,000 + Benefits Want to see your models shaping real business decisions across Europe?
We're looking for a talented and ambitious Data Scientist to join our client's fast-growing Decision Intelligence team, where you'll help shape the future of how data fuels value across the EU business.
This isn't just another data role - it's a genuine chance to be at the centre of a large-scale transformation, designing, building, and deploying advanced machine learning products that impact thousands of customers and change the way intelligence, efficiency, and innovation come to life.
From proof-of-concept to production-ready deployment, you'll work across the full lifecycle using a modern, best-in-class stack (Python, SQL Server, Databricks, MLflow, Azure Machine Learning, Azure Data Lake, and more).
If you're someone who thrives on solving complex problems, loves experimenting with new approaches, and enjoys turning insights into actionable business impact - this is the kind of environment where you'll shine.
You'll be doing things like: Designing, developing, and enhancing predictive models and machine learning solutions that power core EU products and deliver real-world value.
Experimenting with advanced techniques - from regression and tree-based methods to clustering, time-series forecasting, and deep learning - to tackle business-critical challenges.
Turning data into action by providing pricing intelligence and market insights that influence decision-making across multiple European markets.
Partnering with stakeholders across the business to spot new opportunities where data science can unlock efficiency, value, and innovation.
Deploying models into production using cloud infrastructure (Azure), ensuring scalability, robustness, and ongoing performance monitoring.
Championing best practice in data quality, pipelines, and governance to ensure accuracy and trust in every model.
Acting as a mentor to junior team members, sharing knowledge and fostering a culture of curiosity, collaboration, and continuous learning.
What we're after: Proven experience with statistical programming languages (Python or R), and confident working with core data science libraries (NumPy, Scikit-learn, Pandas, TensorFlow, Keras, PyTorch, XGBoost).
A strong foundation in machine learning methods - both supervised and unsupervised - such as logistic regression, GLMs, decision trees, clustering, and deep learning.
Hands-on experience working with SQL to extract, transform, and manipulate datasets.
Exposure to building and managing end-to-end data pipelines for training, evaluation, and reporting.
Familiarity with deploying models into production on cloud platforms (ideally Azure Machine Learning / Azure Kubernetes Services).
An interest in visualisation tools (Power BI) to track and communicate model performance in a clear and engaging way