Data Scientist
Accenture Technology powers our clients to achieve high performance. We combine business and industry insights with innovative technology to drive growth for your business. We extend our technology and business capabilities through a powerful alliance ecosystem of market leaders and innovators to provide our clients the best specialized skills and tailored solutions.
Job Summary
We are seeking qualified Data Scientists to 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.
Qualifications
Strong proficiency in Python, including NumPy, pandas, and scikit-learn, with basic knowledge of PyTorch or TensorFlow
Solid experience in exploratory data analysis (EDA) and feature engineering
Strong foundation in statistics and probability, including hypothesis testing, inference, and distributions
Experience building, evaluating, and tuning supervised and unsupervised machine learning models
Proficiency in SQL for data analysis and querying
Experience with ML experimentation and tracking tools such as MLflow, Weights & Biases, or Databricks ML
Understanding of model evaluation and validation strategies, including cross-validation, metrics, and overfitting
Basic knowledge of cloud-based ML platforms such as Azure ML, AWS SageMaker, or GCP Vertex AI
Experience with data visualization libraries (Matplotlib, Seaborn, Plotly) and BI tools (Power BI or Tableau)
Understanding of MLOps fundamentals, including model versioning, registries, and deployment lifecycle
Responsibilities
Explore, clean, and prepare data for analysis and modeling
Design, build, and evaluate statistical and machine learning models
Run structured experiments and validate results using sound scientific methods
Document methodologies, assumptions, metrics, and key decisions
Communicate insights and results clearly to both technical and business audiences
Collaborate closely with Data Scientists, Data Engineers, ML Engineers, Product Owners, and Subject Matter Experts
Support MLOps handover by providing deployment artifacts and model documentation
Monitor model performance and data drift, contributing to retraining and improvement plans
Ensure alignment between analytical solutions and business objectives
Nice to Have
Experience working in cross-functional, agile environments
Exposure to large-scale or production-grade ML systems
Familiarity with data governance, privacy, or compliance requirements
Previous experience mentoring junior Data Scientists or leading analytical initiatives
Advanced knowledge in a specific domain (e.g., finance, marketing, operations, risk, or customer analytics)
Additional Information
Location: Lisbon
Working Model: Hybrid
Lisbon
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