Job Summary: Develop, validate, monitor, and document statistical models to assess the credit portfolio’s risk level, working with large volumes of data and programming. Key Responsibilities: 1. Development and validation of statistical credit risk models. 2. Analysis and programming in SAS, Python, and/or R. 3. Construction and validation of large-volume databases. **Location:** MEXICO CITY, Ciudad de México, MX **Category:** Risk and Credit **Requisition ID:** 120658 **Internal Models Manager** **(Santa Fe, CDMX)** At Banorte, we seek unique, strong, and extraordinary talent to drive the country’s transformation and innovation, becoming a powerful ally for robust growth with Mexico. We firmly believe that the combination of solidarity, innovation, respect, loyalty, and responsibility is the perfect formula to become the best team in the financial sector. **Job Objective:** Development, Validation, Monitoring, and Documentation of Statistical Models for Assessing the Credit Portfolio’s Risk Level. Each day, you will face **new and interesting challenges** in your role, for which you will be responsible for: * Constructing databases and validating data quality (with focus on large volumes of data). * Analysis and programming in SAS and/or Python/R: writing code and interpreting results. * Developing statistical credit risk models (integrating various statistical techniques to ensure model reliability). * Documenting models (preparing PowerPoint presentations and Word documents with sufficient detail to enable third-party replication of the models). **Requirements:** * Academic background: Bachelor’s degree in Mathematics, Actuarial Science, or Data Science. * Years of experience: 1 year in the financial sector (preferred). * Areas of expertise: Risk, Statistics. * Required knowledge: Structured programming (e.g., SAS, Python, R, SQL, Visual Basic, Office suite). * Languages: English (reading comprehension). * Willingness to travel: Not required. * Willingness to relocate: Not required. At Banorte, we operate under a principle of equal opportunity. Therefore, we do not discriminate based on age, ethnic origin, nationality, gender, sexual orientation, marital status, social condition, health status, religious beliefs, political doctrine, or disability.