• Contributed to dynamic teams focused on leveraging Generative AI and advanced computer vision techniques to transform document processing by extracting relevant data from specific fields.• By extracting and synthesizing valuable information from various documents, I contributed to the enhancement of data ingestion and information retrieval processes.• My participation helped to build a cutting-edge tool that leverages prompt engineering techniques to ensure efficient information extraction, delivering significative value to the project and our stakeholders.• Built the copy detector module which efficiently identified and deleted up to 75% of repeated information, which led to a substantial increase in cost savings for end customer.• Developed prompt engineering strategies that enhanced model accuracy reaching 96%, significantly improving project outcomes and client satisfaction.

• Professor of the Master's Degree in Data Science (online), teaching courses on Artificial Intelligence, Data Science and Business Intelligence.• Master's thesis advisor and supervisor of projects related to Data Science.

• Spearheaded the enhancement of OpenAI LLMs conversational fluency through the development and optimization of prompts using GenAI, resulting in significant improvement in chatbot performance• Pioneered the creation of [PizzaAI] and [VetAI], highly successful conversational agents that leverage Generative AI concepts, applications include Pizza ordering and Vet appointment chatbots• Produced groundbreaking research on intelligent chatbots, applying expertise in prompt engineering, conversational agent design, and cutting-edge technologies (Langchain, LLMs, ChatGPT)• Demonstrated a track record of innovation, consistently improving Generative AI model performance and contributing to advancements in intelligent conversational agents• Led the development and implementation of generative AI strategies, independently defining and executing research projects involving LLM models and applications.

- Experience in utilizing ChatGPT to provide support and assistance to the company.- Responsible for the digital transformation process through the application of data science.

• Performed NLP task for Named Entity Recognition (NER) in Web scraped text data with accuracy of 70% for partial text matches.• Implemented a Relation Extraction Model to detect company names using a BERT trained model.• Conducted web scraped text data cleansing and preprocessing, including the analysis of multilingual data.• Presented results to stakeholders, communicating results professionally and clearly.• Involved in diverse stages of the project including: Snowflake use for diverse database tasks, Deep Learning Hyperparameters tuning, research of state-of-the-art techniques, AWS Containers setup.

• Selected and applied data extraction APIs to obtain georeferenced tweets in different time intervals.• Applied diverse NLP techniques to obtain insights from COVID-19 related tweets such as Topic Extraction and Sentiment Analysis• Implemented a dynamic time-series visualization chart to plot the results of grouped sentiment analysis score obtained from daily consensus in COVID-tweets.• Performed exploratory data analysis to find insights in emergency records for the Secretary of Health.• Used exploratory data analysis to find insights in Electronic Health Records coming from heterogeneous data sources using Python tools• Performed research of ML methods that allow finding patterns in health data using several data sources.

• Participation in Data Science projects involving AI methods and NLP techniques.• Active member of international teams integrated in National Statistical Offices for the use of AI & ML.• Responsible for AI projects carrying out the direction and supervision of the work plans.

• Implementing stock market forecasting method based on Sentiment Analysis and NLP focused on news media.• Development of multivariate time series forecasting models using Deep Learning algorithms and Statistical approaches. • Implementation of time series clustering techniques for customer segmentation.• Exploratory data analysis using statistical tools.• Development and implementation of web scraping tool for news media data collection.• Data Science Project Management • Scientific and technical documenter.

• During doctoral research I identified problems to apply ML, NLP & BD solutions for data processing.• Created a model to find the level of user satisfaction in hotel reviews applying sentiment analysis techniques.• The model was evaluated in Big Data and non-Big Data platforms to compare the accuracy of ML classifiers in both environments.• The ML models reached 92% of accuracy prediction for a solution involving binary text classification

• Contributed in a project for a large banking company to automatically detect relationships between banking operations records coming from diverse data sources, involving quantitative financial data.• Developed data cleaning/preparation methods for further data analysis.• Designer of machine learning models including dimensionality reduction (PCA) techniques• Improved the forecasting accuracy reaching up to 89% to lessen manual tasks.

• Technical writer and documenter in English/Spanish of project proposals to fund research in technology.• Built and designed diverse interfaces in a web prototype for the ministry of education.

• Designed and taught courses for undergraduates as Programming Languages or Software Engineering.• Conducted research projects in IT for education.