Description: Essential: * Bachelor’s degree in Mathematics, Statistics, Engineering, Economics, or related fields; * Practical expertise in statistical modeling; * Experience/proficiency in Python and SQL; * Advanced proficiency in Excel. Preferred: * Completed postgraduate degree or MBA in related fields; * Familiarity with Databricks and/or PySpark; * Experience programming in Power BI; * Prior experience in financial institutions; * Experience developing models compliant with Resolution 4,966/21 or the Internal Ratings-Based (IRB) approach. On-site, hybrid, or remote work; Perform data processing, organization, and integration from multiple sources; Develop and maintain data pipelines to feed statistical models and monitoring dashboards; Lead variable construction processes (feature engineering); Apply statistical and machine learning techniques to analyze large volumes of data, identifying relevant patterns and trends; Develop mathematical/statistical and machine learning predictive models focused on credit risk (PD, EAD, LGD); Ensure model compliance with current regulatory requirements; Monitor model performance and propose continuous improvements; Create and track risk, efficiency, and performance indicators for rules and models; Collaborate with technical and business areas, translating technical concepts for diverse audiences; Ensure proper support for internal, external, and regulatory audits; Share knowledge, promote risk culture, and exchange experiences in a collaborative environment. 2512070202191651670