Statistical Modeling Analyst II – Focus on Risk Modeling

Description

Job Summary: A professional to develop and maintain statistical models and data pipelines, applying advanced techniques for risk analysis and monitoring, ensuring regulatory compliance. Key Highlights: 1. Applying statistical modeling and machine learning in credit risk 2. Developing data pipelines and feature engineering 3. Collaborating with technical and business areas, sharing knowledge Description: Essential requirements: * 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 qualifications: * Completed postgraduate program or MBA in related fields; * Familiarity with Databricks and/or PySpark; * Experience programming in Power BI; * Prior experience working at financial institutions; * Experience developing models compliant with Resolution No. 4,966/21 or the Internal Ratings-Based (IRB) approach. Work mode: On-site, hybrid, or remote; Process, organize, and integrate data from multiple sources; Develop and maintain data pipelines to feed statistical models and monitoring dashboards; Lead feature engineering processes; Apply statistical and machine learning techniques to analyze large volumes of data, identifying relevant patterns and trends; Develop predictive mathematical/statistical and machine learning models focused on credit risk (PD, EAD, LGD); Ensure model compliance with applicable 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 preparation for internal, external, and regulatory audits; Share knowledge, promote risk culture, and exchange experiences in a collaborative environment. 2512100202181911749