Sobre mim:
An analytical, curious professional focused on efficient problem-solving. I have experience in sales, finance, and developing exploratory data analysis projects with Python, data dashboards, SQL, machine learning for financial fraud detection, among other areas, Cloud computing and Big Data, with projects published on Github.
Resumo da experiência profissional:
Data Analyst & Financial Services Specialist with hands-on experience in SQL, Python, data visualization, and machine learning. Strong foundation in data analysis, business insights, and compliance, with practical project experience in credit analysis, fraud detection, and public health data visualization.
Key Data Projects
? Credit Data Exploration with SQL
Explored customer behavior from a credit card dataset using SQL and Amazon Athena. Created external tables via DDL and performed multiple queries using DQL (e.g., SELECT, GROUP BY, ORDER BY) to generate insights. Used aggregation functions like AVG, COUNT, and SUM to uncover patterns in spending and credit utilization.
? Corporate Fraud Detection Model
Built a fraud detection model using Python (Google Colab) and a Kaggle dataset of financial transactions. Handled full ETL, data cleaning, and exploratory analysis. Applied machine learning to classify transactions as fraudulent or not, aiming to improve compliance and prevent financial loss.
? Interactive COVID-19 Dashboard
Developed an interactive dashboard to track the spread and impact of COVID-19 in Brazil using Python, public health data (Johns Hopkins & Oxford), and Looker Studio. Cleaned and transformed data to calculate moving averages, death rates, and vaccination metrics. Highlighted regional disparities and the correlation between vaccination efforts and reduction in cases/deaths. Delivered a visual tool to support data-driven public health decisions.
Key Data Projects
? Credit Data Exploration with SQL
Explored customer behavior from a credit card dataset using SQL and Amazon Athena. Created external tables via DDL and performed multiple queries using DQL (e.g., SELECT, GROUP BY, ORDER BY) to generate insights. Used aggregation functions like AVG, COUNT, and SUM to uncover patterns in spending and credit utilization.
? Corporate Fraud Detection Model
Built a fraud detection model using Python (Google Colab) and a Kaggle dataset of financial transactions. Handled full ETL, data cleaning, and exploratory analysis. Applied machine learning to classify transactions as fraudulent or not, aiming to improve compliance and prevent financial loss.
? Interactive COVID-19 Dashboard
Developed an interactive dashboard to track the spread and impact of COVID-19 in Brazil using Python, public health data (Johns Hopkins & Oxford), and Looker Studio. Cleaned and transformed data to calculate moving averages, death rates, and vaccination metrics. Highlighted regional disparities and the correlation between vaccination efforts and reduction in cases/deaths. Delivered a visual tool to support data-driven public health decisions.
Habilidades:
- Big Data
- Power BI
- Python
- SQL
Áreas de interesse:
- Banco de Dados
- Pesquisa de Mercado
- Cloud Computing
- Planilhas e Relatórios
- Entrada de Dados
