Docente de Maestría de Inteligencia de Negocios

Lead the company on the path of having data-driven customer relationship practices and predictive models, while supporting the launch of new digital businesses for the Mexico and Colombia markets.Coordinate Business Intelligence, Data Science and Data Engineering teams at regional level for best practices and strategic alignment for business goals.

Lead strategic analysis of enterprise data, analysis of all areas of the business. Establish, plan, secure and set structural bases. Contribute to improve the operation, planning and profitability of the company. Lead the data scientist and BI teams to lead permoda to become a data driven company.

♦ Design, development, implementation, and monitoring of business strategies based on data analytics, oriented to the client desk, managing to generate incremental income of up to 15% of the annual budget.♦ Implementation of advanced analytical models for asset price forecasting and following, to optimize decision making in investment portfolios.♦ Creation of the data science team at treasury level, generating an analytics franchise model, promoting the entity to be a data-driven company.♦ Coordination and joint work with the different areas of the treasury in the design and optimization of the models, monitoring and analysis of indicators, using statistical and financial tools.

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♦ Design, development, and implementation of revenue optimization models with market information to search for incremental revenue without modifications to the route network, managing to map up to 18% in incremental revenue for the first year.♦ Design, development, and implementation of an optimization model for the route network of the cargo fleet. ♦ Design and modeling of commercial KPI at the company level, as well as their conciliation with the commercial and operations area. ♦ Optimization of business processes with an impact on resource efficiency and reduction in execution times.♦ Generation of reporting in general for regulatory entities, commercial and operational areas through automated models, minimizing human error.

Development and implementation of a web system for epidemiological surveillance at the department level.