Data Scientist
Accenture
Lisbon, United States of America
6 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
EnglishJob location
Remote
Lisbon, United States of America
Tech stack
Artificial Intelligence
Amazon Web Services (AWS)
Data analysis
Cloud Computing
Data Governance
Data Visualization
Statistical Hypothesis Testing
Python
Machine Learning
NumPy
Power BI
TensorFlow
Azure
SQL Databases
Tableau
Strategies of Testing
Feature Engineering
PyTorch
Model Validation
Pandas
Matplotlib
Scikit Learn
Plotly
Machine Learning Operations
Software Version Control
Databricks
Job description
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., * 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
Requirements
- 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, * 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)
About the company
Accenture is a leading global professional services company that helps the world's leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services-creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world's leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and
build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.