Academic Background
Executive-oriented education focused on real-world decision-making: corporate finance and controllership in regulated environments, and applied data science for operational risk — grounded in Economics.
Open the main card and expand “About the Program” or “Research & Thesis” if you want deeper details.
MBA — Finance & Controllership (USP/ESALQ)
May 2021 – Jan 2023 Valuation · Controllership · Corporate Governance · Regulated CAPEX
MBA — Finance & Controllership (USP/ESALQ)
May 2021 – Jan 2023 Valuation · Controllership · Corporate Governance · Regulated CAPEX
About the Program
This MBA strengthened advanced corporate finance practices, strategic controllership, governance frameworks and investment evaluation — with emphasis on measurable decision-making and disciplined execution in regulated sectors.
Faculty highlights: renowned professors including Alexandre Assaf Neto, a leading authority in Corporate Finance, and Fabiano Guasti Lima, with strong quantitative finance background.
Research, Thesis & Publication
The thesis investigated the relationship between regulatory IRR compliance (CAPEX) and economic-financial indicators in power distribution companies, seeking empirical evidence of how investment discipline can be reflected in corporate performance. The model used OLS regression and structured the dataset for predictive analysis.
The publication derived from the study (Revista GeSec) reinforces the connection between regulatory WACC, CAPEX decision-making and financial results, indicating strong correlations with EBITDA and suggesting that compliance targets can be translated into financial performance targets — exactly the kind of bridge between finance and management that the MBA aims to build.
Acknowledgements to advisor Prof. Igor Gimenes Cesca for academic guidance and methodological rigor.
MBA — Data Science & Analytics (USP/ESALQ)
Apr 2021 – Dec 2022 Poisson · MCA · R · SQL · Python · Applied Analytics
MBA — Data Science & Analytics (USP/ESALQ)
Apr 2021 – Dec 2022 Poisson · MCA · R · SQL · Python · Applied Analytics
About the Program
Advanced training in statistical modeling, machine learning and data-driven decision-making applied to real business environments.
Faculty included Luiz Paulo Fávero, Gino Terentim (Agile/Scrum specialist), and Fabiano Guasti Lima.
Research & Thesis
The thesis studied the correlation between meteorological phenomena and power supply interruptions, using a dataset focused on Maranhão (e.g., São Luís and Imperatriz). The proposal aims to structure a statistical framework capable of anticipating operational risks and guiding preventive actions.
Methodologically, the study employs Poisson regression and Multiple Correspondence Analysis (MCA), implemented in R/RStudio with database processing in SQL Server, connecting statistical rigor with a practical data pipeline.
My MBA thesis in Data Science & Analytics evolved into an applied proposal that received 2nd place in the Innovation Agents program at Grupo Equatorial Energia. The same academic training provided me with practical knowledge of agile methodologies and value-driven project delivery, also supporting the implementation of the New Loc10 Project.
Supervised by Ana Julia Righetto.
Undergraduate Degree — Economics (UFMA → UniCEUMA)
Aug 1998 – Dec 2003 Economic Theory • Econometrics • Quantitative Analysis • Applied Economics
Undergraduate Degree — Economics (UFMA → UniCEUMA)
Aug 1998 – Dec 2003 Economic Theory • Econometrics • Quantitative Analysis • Applied Economics
About the program
Economics degree initiated at the Federal University of Maranhão (UFMA) and completed at Universidade CEUMA (UniCEUMA), with a strong quantitative foundation in economic theory, econometrics, and applied analysis — principles that now support my professional work in regulatory finance, analytics, and investment decision-making.
The undergraduate thesis examined the evolution of e-commerce in Brazil and its potential impact on businesses in the state of Maranhão, anticipating transformations that would later materialize with the expansion of the digital economy.