Data Scientist – Machine Learning & Analytics

About the role

Accenture is looking for Data Scientists to join its technology consulting team in Lisbon. You will develop analytical and machine‑learning models that generate measurable business value while collaborating with Data Engineers, ML Engineers and product owners.

Key responsibilities

• Explore, clean and prepare data for analysis and modeling.
• Design, build, evaluate and tune statistical and machine‑learning models.
• Run structured experiments, validate results and document methodologies.
• Communicate insights to technical and business audiences.
• Collaborate with cross‑functional teams to ensure successful model operationalisation.
• Provide deployment artifacts and documentation for MLOps hand‑over.
• Monitor model performance, detect data drift and support retraining plans.

Required profile

• Strong proficiency in Python (NumPy, pandas, scikit‑learn) and basic knowledge of PyTorch or TensorFlow.
• Solid experience in exploratory data analysis, feature engineering and statistical testing.
• Proven ability to build, evaluate and tune supervised and unsupervised ML models.
• Proficiency in SQL for data querying and analysis.
• Familiarity with ML experimentation tools such as MLflow, Weights & Biases or Databricks ML.
• Understanding of model evaluation, cross‑validation and over‑fitting mitigation.
• Knowledge of cloud‑based ML platforms (Azure ML, AWS SageMaker, Fabric, GCP Vertex AI).
• Experience with data‑visualisation libraries (Matplotlib, Seaborn, Plotly) and BI tools (Power BI or Tableau).
• Basic grasp of MLOps concepts including model versioning and deployment lifecycle.

Required skills

• Python
• NumPy
• pandas
• scikit‑learn
• PyTorch
• TensorFlow
• SQL
• MLflow
• Weights & Biases
• Databricks ML
• Azure ML
• AWS SageMaker
• Fabric
• GCP Vertex AI
• Matplotlib
• Seaborn
• Plotly
• Power BI
• Tableau

What we offer

• Hybrid work model based in Lisbon.
• Opportunity to work on high‑impact projects for global clients.
• Access to a broad ecosystem of technology partners and learning resources.