We are seeking qualifiedData Scientiststo join our team. This role is responsible for developing analytical and machine learning models that deliver measurable business value. The Data Scientist plays a key role in early and intermediate stages of analytical maturity, collaborating closely with Data Engineers and ML Engineers to ensure successful operationalization. We are open to candidates at different levels of seniority.QualificationsStrong proficiency in Python, including NumPy, pandas, and scikit-learn, with basic knowledge of PyTorch or TensorFlowSolid experience in exploratory data analysis (EDA) and feature engineeringStrong foundation in statistics and probability, including hypothesis testing, inference, and distributionsExperience building, evaluating, and tuning supervised and unsupervised machine learning modelsProficiency in SQL for data analysis and queryingExperience with ML experimentation and tracking tools such as MLflow, Weights & Biases, or Databricks MLUnderstanding of model evaluation and validation strategies, including cross-validation, metrics, and overfittingBasic knowledge of cloud-based ML platforms such as Azure ML, AWS SageMaker, or GCP Vertex AIExperience with data visualization libraries (Matplotlib, Seaborn, Plotly) and BI tools (Power BI or Tableau)Understanding of MLOps fundamentals, including model versioning, registries, and deployment lifecycleResponsibilitiesExplore, clean, and prepare data for analysis and modelingDesign, build, and evaluate statistical and machine learning modelsRun structured experiments and validate results using sound scientific methodsDocument methodologies, assumptions, metrics, and key decisionsCommunicate insights and results clearly to both technical and business audiencesCollaborate closely with Data Scientists, Data Engineers, ML Engineers, Product Owners, and Subject Matter ExpertsSupport MLOps handover by providing deployment artifacts and model documentationMonitor model performance and data drift, contributing to retraining and improvement plansEnsure alignment between analytical solutions and business objectivesNice to HaveExperience working in cross-functional, agile environmentsExposure to large-scale or production-grade ML systemsFamiliarity with data governance, privacy, or compliance requirementsPrevious experience mentoring junior Data Scientists or leading analytical initiativesAdvanced knowledge in a specific domain (e.g., finance, marketing, operations, risk, or customer analytics)Additional InformationLocation: LisbonWorking Model: Hybrid#J-18808-Ljbffr