Enlighten Data Story: iFood
A scientific approach to A/B Testing and statistical significance to validate marketing strategies and prevent budget waste using Python and Power BI.
From Python automation to strategic Power BI Dashboards. Technology applied to solve complex tax problems.
A scientific approach to A/B Testing and statistical significance to validate marketing strategies and prevent budget waste using Python and Power BI.
Transactional audit of 169,000 contracts to fix a BRL 130M structural deficit in legacy models and propose Risk-Based Pricing policies.
Predictive AI engine using K-Means to resegment a health insurance portfolio, eliminating cross-subsidization and achieving a strict 75% target loss ratio via Power BI.
Random Forest predictive model built in Python to mitigate bank churn, translating complex behavioral patterns into a Power BI Executive Dashboard focused on revenue protection.
Application of an unsupervised algorithm (K-Means) to a 45,000-student base to map behavioral profiles, isolate financial friction, and mitigate a churn risk of 9,626 subscriptions.
Predictive & prescriptive labor analytics PoC using real TRT5 rulings. Audited BRL 1M+ in risk, mapped witness‑driven loss probabilities, and reverse‑engineered a litigation‑proof employment contract with a local LLM (Qwen2.5).
Data Analytics and AI case study explaining why revenue grew while margin declined. Includes an interactive HTML/CSS/JS dashboard, semantic search, granular filters, anonymized data, and a profitability recovery simulator.