About the Company
At Sourcing Trust, we are committed to delivering innovative, reliable, and tailored technology solutions that empower businesses to succeed in a rapidly evolving digital landscape. With a focus on excellence, integrity, and collaboration, we build lasting partnerships by understanding our clients' unique needs and providing them with expert support across. Our team is dedicated to fostering a positive and inclusive work environment where every employee's contribution is valued, encouraging continuous growth, learning, and shared success. Join us and be part of a passionate organization driven by innovation and excellence.
About the Role
We are looking for a Mid Data Scientist with strong Python expertise and proven experience building production-level ML models through EDA, feature engineering, model development, and evaluation. The role requires solid statistical foundations, proficiency in ML experimentation tools and MLOps fundamentals, and the ability to deliver actionable insights to technical and non-technical stakeholders across diverse data science environments.
Requirements
Requirements
Strong knowledge of Python (NumPy, pandas, scikit-learn; 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 strategies (cross-validation, metrics, overfitting prevention).
Basic familiarity with cloud ML platforms (Azure ML, AWS SageMaker, GCP Vertex AI).
Experience in data visualization using Matplotlib, Seaborn, Plotly, and BI tools (Power BI, Tableau).
Understanding of MLOps fundamentals (model registry, versioning, deployment lifecycle).
Soft Skills
Exceptional analytical thinking and problem-solving capabilities.
Ability to clearly explain technical insights to technical and non-technical stakeholders.
Collaborative mindset for integration across multiple Data teams.
Structured, value-oriented approach to problem-solving.
Adaptability to new data, requirements, and project scenarios.
Takes full ownership of the analytical lifecycle and model quality/reliability.
Proactive communication skills to simplify technical concepts for diverse audiences.
Experience
Degree in Mathematics, Computer Science, Machine Learning, or related field.
3-5 years of professional experience in data science environments, building and deploying production-level models.
Language Requirements
English proficiency minimum B2 (mandatory).
Portuguese fluency (mandatory).