Renier Medina Canche

Actuario con Maestría en Tecnologías de la Información e Inteligencia Analítica con más de 7 años de experiencia en el sector Bancario en el área analítica de Riesgo de Crédito, ayudando a las Instituciones a tomar decisiones basadas en el análisis de datos.

Over the past 6 years, I've worked at one of Mexico's largest banks, Citibanamex, in the Risk Analytics department where:

☑ I conducted ETL processes in SAS with SQL programming for calculating the general standard methodology (logistic regression model) for regulatory loan loss reserves of Credit Card, Personal Loans, Payroll, Auto, and Mortgage portfolios in accordance with the Circular Única de Bancos (CUB) from the National Banking and Securities Commission (CNBV, local Regulator).

✅ I handled and provided follow-up on risk model audits (reserves) from CNBV, Banco de México (Banxico, Central Bank), Internal Audit (IA), and External Audit (KPMG) using SAS, Microsoft Excel, and Word.

✔ I prepared materials related to risk models (reserves) for the Risk Committee, Board of Directors, and Senior Management in SAS, Microsoft Excel, Word, and PowerPoint.

🤝 I collaborated closely with other departments to work as a cohesive team: Data & Analytics, Accounting, Finance, Controllers, Corporate Treasury, Regulatory Reporting, MIS, etc.

👐 I served as a manager leading a dynamic and committed team, delivering results in a timely manner.

💪 I worked under constant pressure (prioritizing activities), with notable instances during the COVID-19 pandemic and analyses related to the institution's sale, as well as regulatory changes due to IFRS9 and changes in leadership.

🤓 I earned the trust and confidence of my direct supervisors, including the Director and Deputy Director of Credit Risk Models, based on detailed data analysis and excellent adaptation to daily challenges. They can provide references at any time.

Actuario con Maestría en Tecnologías de la Información Inteligencia Analítica, graduado con honores con un proyecto de titulación aplicando modelos de machine learning, además de obtener diplomas en Machine Learning, Data Science y Data Mining en R y Python.