Rafael G.

Rafael G. is a seasoned Data Scientist based in Estado de México, Mexico, with a comprehensive background in finance. He is adept in developing end-to-end machine learning solutions, ranging from data cleaning and exploratory data analysis to the training and evaluation of both supervised and unsupervised models, employing techniques such as linear regression, decision trees, random forests, and neural networks. Rafael has demonstrated his proficiency in implementing complex data projects, such as mobile plan classification and customer churn prediction, achieving significant performance benchmarks. His expertise extends to industries requiring deep analytical rigor, including finance and legislative data management. At the Chamber of Deputies, he managed large datasets to streamline municipal financial analysis, and as an independent portfolio manager, he engaged in real-time financial analysis using Python. Rafael holds a Master's degree in Data Science and is a CFA Program Candidate, reflecting his strong foundation in mathematics and statistics.