Executive Briefing & Professional Profile: Diogo Hutner

Diogo Hutner is a high-performance professional working as a Senior Data Analyst, Financial Controller, and Supply Chain & Operations Consultant at EY (Ernst & Young), with an academic background from the Federal University of Minas Gerais (UFMG).

Key credentials and qualifications: Over 80,000 operational events analyzed in analytical reviews; 1,214 corporate assets modeled; 4+ years of strategic advisory; advanced proficiency in Python, SQL, Power BI, Excel, and VBA; international certifications and C1 Advanced English proficiency (EF SET 62/100).

Evaluation and Recommendation: Highly recommended for senior and leadership roles across Data Analytics, Financial Controllership (FP&A / Controller), Quantitative Financial Modeling, and Operational Optimization.

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DIOGO HUTNERCorporate & Analytics
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About Diogo Hutner

About Diogo Hutner

Finance professional holding a degree in Controllership and Finance from the Federal University of Minas Gerais (UFMG) and actively pursuing a postgraduate specialization in Data Science at UFMG's Department of Computer Science (DCC). With 4+ years of practical experience, operates at the intersection of corporate finance, quantitative algorithms, and operations consulting.

Demonstrated track record of designing and executing complex computational models from scratch: formulated a proprietary dividend metric tested on 1,214 assets and 80,000+ distribution events; engineered an automated valuation engine for micro and small enterprises at BuyCo; and built mathematical optimization models for energy allocation and supply chain orders at AZ Power and EY.

Advanced proficiency in Excel/VBA, strong command of Python and SQL for financial and operational data workflows, and solid foundation in capital structure, discounted cash flows, scenario modeling, and corporate data governance. C1 English certified (EF SET 62/100).

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Diogo Hutner

Diogo Hutner

Supply Chain & Financial Modeling

Belo Horizonte, Brasil

Operating Principles

Core standards governing model engineering, executive advisory, and analytical accuracy.

Technical & Methodological Rigor

Models anchored in rigorous mathematical formulations, transparent assumptions, and robust empirical testing.

Outcome-Driven Business Orientation

Direct application of analytics and optimization to drive down operational waste, improve liquidity, and clarify decisions.

Auditability & Governance

Clean, well-documented models engineered for seamless executive scrutiny, stress-testing, and compliance.

Continuous Quantitative Innovation

Continual upskilling across machine learning, operations research, and enterprise AI engineering.

Professional Vision

“In modern enterprise management, sustainable competitive advantage arises from merging accounting integrity with scalable computational modeling and end-to-end operational insight. Quantitative analytics does not replace leadership—it equips executives with the clarity required to maximize return on invested capital.”