Through the role of Research Engineer (Data Analyst) at SDAS Research Group , I have developed Data Analysis techniques and AI models across various research fields. I also assist in developing and writing Academic Research products to support data-driven decision-making. Key Achievements :- Successfully merged ideas from different stakeholders. - Published at least one article a year (total of 8)- Involved in 5+ projects

As Data Analyst, I worked on the consolidation, processing, management and modeling of environmental, hydrological, and weather data. These Data Analytics task supported decision-making for the conservation, protection, and maintenance of water sources. Key Achievements :- Applied analytical methods, data visualization and statistical analysis to 10+ hydro-metric stations_ Designed and coded 20+ mathematical models in Python &R to analyze datasets- Presented data findings to support business goals and address challenges for 2 institutions

As a Data Analyst, I conducted hydrology and hydro-meteorological data analysis, accessed Linux servers, and executed meteorological models (WRF). I designed and coded AI and ML models, providing technical insights on machine learning techniques to enhance product prototypes. My role involved meteorological data analytics, data visualization using Python, and statistical analysis, with a focus on Big Data applications for Quito’s water sources. I performed data entry, processing, manipulation, cleaning, aggregation, and analysis, and reviewed and edited technical software documentation for various projects. Additionally, I applied computer science principles to solve business challenges and support business goals.-Key Achievements:- Employed Big Data to monitor (Microsoft Power BI visualizations) extreme weather events in Quito’s water sources 24/7.- Created, presented, or reviewed 50+ reports, technical software documentation and business-oriented summaries of data-based decisions by government personnel (Word, PowerPoint, Excel, LaTeX)- Internally led requirements elicitation for 1 procurement process, focusing on design and implementation

As a Intern at Estacion Cientifica Agua y Paramo (ECAP) I worked on the identification of key variables for precipitation forecasts in Quito using data mining techniques for 2 weather stations. I performed feature selection using a Support Vector Machine (SVM) classifier on a dataset with 10 variables. I developed a deep learning network for nowcasting precipitation values, accounting for the spatial-temporal nature of the dataset. This role allowed me to apply the CRISP-DM methodology to execute the life cycle of a data mining project.Key Achievements:- Publication of 1 scientific article.- Proved the usefulness of data-based models to forecast extreme precipitation events.- Creditor for the "Acuerdo de Cooperacion en el Marco de la Estacion Cientifica Agua y Paramo" between SDAS Research Group and "EPMAPS - Empresa Publica Metropolitana de Agua Potable y Saneamiento de Quito", (2020).

As an Intern AI Developer at ATBS S.A., I gathered requirements and developed an AI model for sound classification. My role included Feature Engineering, Data Collection, model optimization, and documentation of methodologies to enhance ML and DL algorithm.Key Achievements :- Handled feature engineering on images extracted from 10+ videos of several sources- Developed a sound classifier model using a dataset with 135 classes and 400 samples per class- Documented and edited (4 documents) the methodologies applied through the internship.