Job Description
PowerTalent: Recruitment, Selection, and Global Outsourcing
PowerTalent stands out for its customized talent solutions. As specialists in recruitment and selection, we streamline complex processes and find the best professionals worldwide.
We offer recruitment, outsourcing, and hybrid solutions, building local, nearshore, or offshore teams according to our clients’ needs.
With PowerTalent, we guarantee complete and efficient solutions, so our clients don’t have to worry about a thing.
New opportunity for a new international Tech Hub emerging from Lisbon.
We are seeking an experienced Mid Data Scientist to contribute to the design and execution of advanced analytical and machine learning solutions.
3+ years of professional experience in data science environments, building and deploying production-level models.
Degree in Mathematics, Computer Science, Machine Learning, or a related field.
Strong knowledge of Python (NumPy, pandas, scikit-learn; with basics of PyTorch/TensorFlow).
Solid experience in Exploratory Data Analysis (EDA) and feature engineering.
Strong foundation in statistics and probability (hypothesis testing, inference, distributions).
Proven experience building and evaluating supervised and unsupervised ML models, including tuning and validation.
Knowledge of ML experimentation tools (MLflow, W&B, Databricks ML).
Proficient in SQL for data analysis and querying.
Understanding of model evaluation and validation strategies (cross-validation, metrics, overfitting).
Basic familiarity with cloud M L platforms (Azure ML, AWS SageMaker, GCP Vertex AI).
Experienced in data visualization using Matplotlib, Seaborn, Plotly, as well as BI tools like Power BI or Tableau.
Understanding of MLOps fundamentals (model registry, versioning, deployment lifecycle).
English proficiency(minimum B2 level).
Soft Skills:
Exceptional analytical thinking and problem-solving capabilities.
Ability to clearly explain technical insights to technical and non-technical stakeholders.
Collaborative mindset to ensure integration across multiple Data teams.
Structured and value-oriented approach to problem-solving.
Adaptable to new data, requirements, and project needs, ensuring appropriate solutions are used in varying scenarios.
Takes full ownership of the analytical lifecycle and ensures the quality and reliability of models delivered.
Proactive communication skills with the ability to simplify technical concepts for diverse audiences.
Contract or B2B, its up to you
Hybrid Work: 2 days per week in the office and 3 days at home.
Continuing education and professional development
