MIS Analyst - Credit & Risk

Description

Job Summary: You will join an analytical team, designing business metrics and reports to support managers in their decision-making, as well as analyzing data and structuring databases. Key Highlights: 1. Be part of an analytical team with Data Engineers and Data Scientists 2. Develop and maintain dashboards in Power BI, Tableau, or similar tools 3. Identify trends and propose data-driven improvements **About the Role** You will join an analytical team composed of Data Engineers, Data Scientists, and Data Analysts. Your responsibilities will include analyzing data, building/developing business metrics to support managers and business analysts in their decision-making; conducting quantitative studies, structuring databases, and preparing executive reports. * **Education** * + Statistics, Computer Science, Mathematics, Information Systems, or related fields. * **Key Responsibilities:** * + Extract and process data from various sources to generate managerial and operational reports; + Develop and maintain dashboards and performance indicator panels using tools such as Power BI, Tableau, or similar. Automate data collection and analysis processes to optimize operational efficiency. + Create and monitor KPIs (Key Performance Indicators) to support management and decision-making. + Ensure the integrity and reliability of data provided to strategic departments. + Identify trends and patterns from data analysis, proposing process improvements. + Support various company departments with data-driven insights and customized reports. * **Requirements** o Professional experience in BI or Analytics, specifically in designing and presenting managerial dashboards for Credit and/or Credit Risk; o Prior experience with Tableau, Power BI, or other BI tools; o Experience monitoring operations, credit portfolio, and credit/collections results (including PDD — Provision for Doubtful Debtors); o Ability to translate business problems into data products; o Proficiency in Python and SQL (mandatory); * **Desirable** o Experience monitoring classification models; o Experience and in-depth knowledge of SIGMA; o Knowledge of statistical techniques and statistical modeling (probability, simulations and forecasting, decision trees, linear regression, predictive analytics, multivariate statistics).