👨💻 About me
- Data Scientist with over 3 years of experience in data, specializing in time series forecasting, causal inference, and spatial analysis using Python.
- I have professional experience in market and business data analysis, which has contributed to the development of strong analytical and data communication skills.
- My Master's degree in Applied Economics provided me with a solid foundation in statistical and mathematical modeling, as well as research skills. My undergraduate degree in engineering developed my ability to solve complex problems and learn autonomously.
- I work on data science projects using Machine Learning models in Python, covering areas such as sales forecasting, demand price elasticity, as well as customer classification and clustering. These projects demonstrate my ability to apply algorithms with best coding practices to extract insights and guide strategic decisions.
Academic Qualifications
- Master's degree in Applied Economics with a focus on time series and spatial econometrics. The thesis employs, among other techniques, autoregressive (VAR) models, vector error correction (VEC) models, and impulse response analysis to examine how Brazil's soybean exports relate to global macroeconomic variables, providing insights into the economic impacts of global changes.
- Bachelor's degree in Agricultural Engineering with a focus on agribusiness. In my final project, I used R to create price forecasting models for major agricultural commodities using the ARIMA methodology, published in the Journal of Economics and Agribusiness.
💻 Experiences
Professional Experience
- Data Analyst and Researcher: CNPq Industrial Technological Development Fellow - Level B, working on research projects related to the expansion of dengue fever in the Brazilian Legal Amazon, identifying spatio-temporal patterns. The work is under development and can be followed through the Github repository.
- Market Analyst: Analyzed the ethanol market for the intelligence sector at Ipiranga, identifying patterns, trends, and contributing to the company's strategic decision-making.
Data Science Projects
- 10+ completed Data Science projects, including Regression, Classification, and Clustering.
- Projects developed with a focus on solving business problems, following the CRISP-DM methodology.
- Projects involving Exploratory Data Analysis, aimed at identifying patterns through descriptive statistics and regression.
Programming Language Experience
- 4+ years of experience in Python, using it for data analysis and developing Machine Learning models, with knowledge of libraries such as Pandas, Scikit-learn, Statsmodels, and Matplotlib.
- 5+ years of experience in R, developing academic works in R and R Markdown, with a focus on time series econometrics and spatial econometrics.
BI Experience
- Proficient in Power BI for creating dashboards and interactive visualizations.
📞 Contact
Feel free to get in touch with me: