👋 Hello! My name is...

Alexsander Lopes Camargos

and I'm a

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Who I am

Greetings! I am a seasoned Brazilian professional, boasting over 15 years of expertise in the administrative domain, now embarking on an exciting transition into data analysis. I possess a deep passion for distilling complexity into clarity, excelling in crafting strategic, data-driven solutions. Armed with a degree in Business Administration and furthering my studies in Economics and Business Intelligence, I am ever eager to embrace new challenges and leverage my knowledge to foster impactful outcomes.

Discover more about my journey.

Resume
Alexsander Lopes Camargos

Here are a few technologies I've been working with recently:

  • Languages & Tools

    • Languages: Python, R, SQL
    • Processing Libraries: PySpark, Pandas, Polars, NumPy, DuckDB
    • Visualization Libraries: Matplotlib, Seaborn, Plotly
    • Business Intelligence: DAX, Power Query M

  • Modeling & Machine Learning

    • Libraries: Scikit-learn, Statsmodels
    • Techniques: Classification, Regression, Clustering, Random Forest, SVM, Gradient Boosting (AdaBoost, XGBoost)
    • Model Validation: Cross-validation, Performance Metrics (Accuracy, Precision, Recall, F1-Score, AUC-ROC)

  • Data Visualization & Storytelling

    • BI Tools: Power BI, Tableau, Looker Studio
    • Code Dashboards: Streamlit, Rill, Evidence
    • Techniques: Data Storytelling, Stakeholder Communication

  • Engineering & Databases

    • SQL Databases: PostgreSQL, MySQL, MariaDB, SQL Server
    • NoSQL Databases: MongoDB
    • Access Tools: Datagrip, DBeaver

  • Cloud & Data Pipelines

    • Cloud Platforms: AWS, Azure, Oracle Cloud
    • Data Platforms: Databricks, MotherDuck
    • Deployment: Vercel, Netlify, Linode

Some Things I've Built

    Featured Project

    Python Fundamentus

    The Python Fundamentus is an API developed in Python designed to facilitate quick access to the main fundamental indicators of the most relevant stocks in the Brazilian market. By utilizing the information available on the Fundamentus website, it provides detailed financial and fundamentalist information of companies listed on B3, this project aims to bring the wealth of financial data directly to your Python applications in an efficient and organized manner.
    • Python
    • Scraping
    • Beautiful Soup
    • Requests
    GitHub PyPI

    Featured Project

    Bacen IF.data AutoScraper & Data Manager

    The Central Bank of Brazil (Bacen) publishes detailed reports on a quarterly basis, featuring a wide range of data about financial institutions, available through the IF.data Portal. Although this data is valuable, it requires careful processing and analysis to extract significant information. The main goal of this project is to apply data mining techniques to the datasets from the IF.data Portal with the aim of creating insights about the Brazilian financial system.
    • Python
    • Selenium
    • pathlib
    GitHub

    Featured Project

    Nobel Prize Master Data

    This project, through a report in Power BI, analyzes Nobel Prize laureates from 1901 to 2019 to explore trends, global recognition, and diversity. Focusing on the geographical distribution, it highlights the leadership of the United States with 272 awards (35.74% of the total), followed by the United Kingdom and Germany, reflecting the dominance of certain nations and the universality of the award. Utilizing Power BI's analytical tools for dynamic and interactive visualization, the project encourages discussion on its findings, underscoring the historical impact of the Nobel Prize and fostering debates on excellence in science, literature, and peace, promoting a deeper understanding of its significance and evolution.
    • Microsoft Power BI
    • Microsoft Power Query
    • DAX (Data Analysis Expressions)
    Preview

    Featured Project

    Space Race

    This project, titled "Corrida Espacial" (Space Race), presents a comprehensive Power BI dashboard analyzing global space missions throughout history, encompassing 4,630 missions with an impressive 89.89% success rate. The visualization highlights the dominance of the USA (1,467 missions) and Russia (1,416 missions) in space exploration, while also tracking contributions from emerging space powers like Kazakhstan, China, and France. On the organizational front, RVSN USSR leads with 1,777 missions, followed by various agencies and companies including CASC, Arianespace, and NASA. The dashboard provides temporal analysis showing mission frequency since 1960, with notable peaks in the 1970s and recent years (reaching 157 missions), alongside geographical launch site distribution and rocket performance metrics covering 370 different rocket models across 62 companies. This interactive tool offers valuable insights into the evolution and current state of humanity's space exploration endeavors, serving as a historical record of our collective achievements beyond Earth.
    • Microsoft Power BI
    • Microsoft Power Query
    • DAX (Data Analysis Expressions)
    Preview

Get In Touch

My inbox is always open. If you want to offer me an opportunity, have a question or just want to say hi, I will try my best you answer you!

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