As a Data Scientist at Coppel, I specialize in the end2end development of predictive models, leveraging Machine Learning and Deep Learning architectures such as LSTM for advanced forecasting and time-series analysis. My role involves conducting rigorous data analysis and hypothesis testing to build supervised and unsupervised models for classification, regression, and clustering, utilizing a technical stack that includes Python, PyTorch, SQL, and TensorFlow. By transforming complex datasets into actionable insights, I focus on optimizing strategic decision-making and driving technological innovation within the company's data science initiatives.