Job Summary: A data professional responsible for developing and maintaining statistical models, analyzing data, and collaborating with teams to ensure regulatory compliance and continuous improvement. Key Highlights: 1. Working with statistical modeling and machine learning 2. Developing predictive models focused on credit risk 3. Collaborating with technical and business teams 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 degree or MBA in related fields; * Familiarity with Databricks and/or PySpark; * Experience programming in Power BI; * Prior experience working in financial institutions; * Experience developing models compliant with Resolution 4.966/21 or IRB. 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 engineering (feature engineering) processes; 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 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 teams, translating technical concepts for diverse audiences; Ensure appropriate responses to internal, external, and regulatory audits; Share knowledge, promote risk culture, and exchange experiences in a collaborative environment. 2512100202181911749
João Silva
Indeed · HR
João Silva
Indeed · HR
