Programming Language
- Python focused on data analysis (Pandas, Numpy, Seaborn, Matplotlib).
I'm a Data Analyst with experience working in fully remote, international environments, where clarity, autonomy, and structured communication are essential. Over the past 3 years, I have helped transform raw data into actionable insights that support strategic business decisions.
My work spans the full data lifecycle — from data extraction, cleaning, and transformation (ETL) to building scalable data models, performing exploratory and statistical analysis, and developing executive dashboards. I focus on writing reliable, reproducible code and creating analytics solutions that are clear, documented, and decision-oriented.
Having collaborated across distributed teams, I value asynchronous communication, ownership, and proactive problem-solving. I am particularly motivated by environments where data drives product, operations, and growth decisions at a global scale.
I see my role as a bridge between data and strategy — translating complexity into clarity and enabling teams to move forward with confidence.
Worked on Artificial Intelligence projects focused on data curation, linguistic quality, and Large Language Model (LLM) training support, ensuring semantic accuracy, native fluency, and data reliability.
Expertise in dataset curation and validation, Portuguese ↔ English translation review, application of Prompt Engineering techniques, and automation of data workflows via APIs, SQL, and Python, resulting in significant gains in quality and operational efficiency.
Experience with annotation, thematic classification, continuous auditing of textual corpora, and data governance practices to support data-driven decision-making.
Worked as a Data Analyst focused on business intelligence, automation of analytical processes, and generation of strategic insights.
Expertise in automating ETL pipelines with SQL and Python and developing interactive dashboards in Power BI, supporting managerial decisions through KPIs and data-driven analysis in multidisciplinary contexts.
In this project, I used Python and Streamlit to develop an interactive dashboard featuring key metrics for a real estate buying and selling company.
Application of Data Science to investigate the impact of smoking on insurance costs, using regression models to estimate medical expenses.
Transactional data analysis to identify behavioral patterns and bottlenecks, combining SQL processing with clear data visualization.
Development of a Machine Learning model to support the identification of Autism Spectrum Disorder (ASD) indicators based on clinical and behavioral data. The project includes exploratory analysis, data preprocessing, and evaluation of predictive models.
Feel free to get in touch.