Henrique PAIN
About me
Competition has always been in my DNA. Through childhood sports, I learned early on that consistency and maximum effort surpass talent.This spirit guided me when I left home at 18 and when I crossed the ocean to live and work on another continent, completely on my own. In my career, this mindset translated into taking on complex management and finance challenges, where I had to be self-taught to deliver results.My goal is clear: to leave any project or company bigger and better than when I found it. I sleep soundly knowing that, in every opportunity, I gave my ABSOLUTE BEST.
study
As I was finishing elementary school, Brazil was at the height of the "20 cents" protests. For the first time, my attention was captured by the barrage of news regarding politics and economics.I decided to delve deeper, and after seeing an elasticity calculation in a news report, I began my studies in economics. From that moment on, 10 years ago, I never stopped.I studied Economics at UPF (Passo Fundo), graduating in 2021, right at the end of the pandemic. Subsequently, I completed two MBAs: one in Business Management and another in ESG.In 2025, I formalized my knowledge with the CPA-20 certification. Throughout the year, driven by work demands, I dove deep into Data Analysis and Database studies, completing dozens of online courses and actively participating in technical communities on Discord and Substack.
projects
n agribusiness, understanding the temporal precedence between weather events and price action is what separates a basic analysis from a robust market strategy. This project evolved from an automated ETL pipeline into a full econometric modeling system that quantifies the real impact of rainfall in the Passo Fundo/RS region.Technical Architecture Highlights:
1- Data Ingestion: Custom web scraping (Noticias Agrícolas) integrated with the Open-Meteo API to consolidate daily price and climate time series.2- Storage: Layered architecture in Google BigQuery, centralizing historical data since 2025.3- Orchestration: Daily automation and pipeline health monitoring via GitHub Actions (CI/CD).4- Econometric Analysis: Applied Granger Causality tests and OLS (Ordinary Least Squares) regression to isolate and quantify variables.5- Visualization: Dynamic Looker
Studio dashboard integrated with a 6-day lead-time forecasting model.The modeling identified a 6-day logistic lag: the regional physical market takes nearly a week to fully absorb supply shocks caused by intense rainfall events.• Statistical Rigor: The model was validated with a p-value of 0.007, indicating a confidence level superior to 99%.• Price Elasticity: Analysis revealed that for every 10mm of accumulated rainfall, there is an average price variation of R$ 1.25 per bag after the 6-day period.• Real-Time Projection: The system generates market opening forecasts for the following Monday based on the current day's precipitation volume.
In this project built with mock data, the goal was to create an easily interpretable dashboard that clearly communicates complex indicators to different organizational levels, without the need for extensive presentations.The project encompasses detailed data from the 2025 Income Statement, as well as organization by macro-categories (Admin, Financial, Personnel...), smart cards that change color according to performance, and finally, charts that demonstrate the weight of accounts and the margin over company revenue.Furthermore, the project presents the 2026 cash flow, as well as analyses of forecast errors that occurred in Dec/24. More details and the BI presentation are in the link below! 🐻
in this analysis with Kaggle data imported via script directly into SQL, the goal was to create a dashboard that allowed the manager to automatically calculate revenue variation according to different price levels, using an elasticity metric.The background was created in FIGMA, so we used 3 distinct tools for this report, the most interesting part being its automatic integration with the SQL database.More details and the BI presentation are in the link below! 🐥
LET'S CONNECT
If you need to transform financial data into clear decisions, send me a message 😺
Centro
Passo Fundo, RS Brasil[email protected]