Senior Cientista de Dados

📋 Description

• Develop, validate, and enhance statistical and Machine Learning models, ensuring performance, stability, and explainability.

• Conduct end-to-end analyses: exploration, preparation, modeling, and delivery.

• Apply predictive modeling techniques, clustering, anomaly detection, and forecasting to business problems.

• Work with large volumes of data, ensuring quality, integrity, and statistical coherence.

• Engage in strategic use cases, translating business needs into data-driven analytical solutions.

• Support the deployment of models into production in collaboration with data engineering and MLOps teams.

• Communicate results and insights clearly to both technical and business audiences.

• Collaborate with multidisciplinary teams (engineering, analytics, product, and business).

⛳️ Requirements

• Experience in predictive modeling, machine learning, and statistical analysis.

• Proficiency in Python and/or R, along with ML libraries (scikit-learn, TensorFlow, etc.).

• Experience with clustering techniques, anomaly detection, and forecasting.

• Preferably familiar with the Databricks platform for ML deployment.

• Ability to translate analytical results into business insights.

• Strong knowledge of SQL for handling and analyzing large data volumes.

• Experience with complementary data science libraries (Pandas, NumPy, XGBoost, PyTorch, or similar).

• Knowledge in feature engineering and preferably experience with Feature Store.

• Experience with PySpark and distributed data processing.

• Familiarity with cloud environments, preferably Azure (Azure ML, ADLS, Data Factory).

• Knowledge of MLOps practices (model versioning, deployment, monitoring), with experience in MLflow or similar tools.

• Ability to conduct analyses autonomously with critical thinking and business acumen.

• Strong communication skills to engage with diverse audiences.

• **Desirable:**

• Experience with transactional data and/or fraud prevention.

• Background in regulated or high-stakes environments.

• Knowledge of visualization tools (Power BI, Tableau, or similar).

• Postgraduate degree, master's, or PhD in quantitative fields (Statistics, Mathematics, Computer Science, Economics, or related fields).

🏝️ Benefits

• Competitive salary based on experience;

• Opportunities for growth within the company and participation in strategic projects;

• Dynamic and challenging work environment;

• Chance to work in a rapidly expanding market company.