Description: * Bachelor's degree in Engineering, Economics, Statistics, Mathematics, Computer Science, and/or related fields. * For internal candidates: minimum of 6 months of experience at Sicredi. TECHNICAL KNOWLEDGE DESIRED FOR THIS POSITION Programming and Tools * Languages for advanced analytics (SQL, R, Python) * Version control and CI/CD tools (Git, GitLab or similar) * ML/AI frameworks (TensorFlow, PyTorch, Scikit-learn) Modeling and Statistics * Advanced statistics applied to data science (inference, hypothesis testing, multivariate analysis) * Statistical and econometric modeling (regressions, time series, survival models) * Experience with production environments (model deployment, MLOps, monitoring) Infrastructure and Data * Experience with cloud platforms (AWS) * Building queries for relational and non-relational databases (advanced SQL, optimization) * Data architecture (modeling, ETL pipelines, integration) * Advanced data visualization and data storytelling (Power BI, Plotly, Seaborn) Governance * Data governance and compliance with LGPD Soft Skills * Clear and objective communication * Empathy and collaboration * Critical and analytical thinking * Problem-solving focus * Conduct scenario studies and business diagnostics; * Develop and support teams in measuring results, identifying opportunities, trends, and patterns in datasets; * Proactively propose hypotheses and solve problems using data science; * Present and communicate analyses in a non-technical manner; * Collaborate with Data Engineers to improve data acquisition and transformation workflows used in models; * Partner with Data Analysts to generate business insights and guide information analysis for optimal strategic decision-making; * Prioritize model quality, performance, and sustainability; * Participate in the Data Science Chapter, encouraging and promoting a data-driven culture among colleagues and teams across our operations; * Maintain necessary documentation for deliverables; * Continuously advance technical and business knowledge; * Understand and apply statistical and machine learning techniques to propose changes, provide answers for decision-making, and embed intelligent models and algorithms into software products; * Extract and process data from diverse sources and at large volumes. 251221020255769963