• Developed a Zero Shot Prompting classification model using LLMs such as GPT 4o, Gemini 1.5 and Llama 3.1, and peforming several prompt engineering techniques, for categorizing bank transactions automatically. This approach leverage 3x faster a model in production environments. • Leveraged OpenAI, Google Vertex and Tesseract tools for Artificial Vision model designed to automatically extract key data from images of invoices and bills.

• Developed interactive dashboards and applications using Shiny, Streamlit, and PowerBI, resulting in a 40% increase in report accessibility.• Skilled in constructing sophisticated machine learning models using technologies such as BERT and GPT for text analysis and predictive analytics, focusing on extracting actionable insights from complex text datasets.• Designed and implemented a web scraping algorithm using Python, BeautifulSoup, and Selenium to automatically download data from online stores, integrating these data into databases via automated ETL processes for streamlined preprocessing.• Fine-tuned BERT and T5 models for automatic classification of vehicle features using internal spreadsheets, categorizing vehicles into company-specific labels to accurately determine interest rates and payment plans.

• Developed comprehensive KPI dashboards in PowerBI and slides, providing real-time business insights that led to a 15% improvement in strategic decision-making.• Enhanced data governance and quality frameworks using Python, Pytorch and Scikit Learn, ensuring compliance with industry standards and reducing data-related errors.• Conducted advanced statistical analysis to identify key performance drivers, translating complex data sets into actionable insights that improved operational efficiency.• Devised and implemented NLP-driven improvement strategies for call center agents, optimizing performance and customer satisfaction through advanced analytics, using Hugging Face models like BERT, T5 and tools such as Pytorch, Tensorflow.

• Developed a machine learning model for price optimization, effectively adjusting vehicle prices based on characteristics and market conditions, enhancing pricing strategy and profitability.• Conducted sentiment analysis using NLP and NLTK on customer feedback, extracting insights to refine vehicle features and enhance customer satisfaction.• Applied econometric techniques and time series with ARIMA models to forecast financial indicators, significantly contributing to informed strategic planning and financial stability.• Analyzed sales trends using Python and pandas, identifying seasonal patterns and accurately predicting future sales, which optimized inventory management and sales tactics.

Customer service bilingüe, para atender clientes de la compañía AT&T en Estados Unidos, tanto en idioma Español como en Inglés.