Sebastián Córdova

I work as a data scientist at ST Analytics, working on projects such as housing price prediction and energy level prediction in residences. In these projects, I have implemented advanced models such as XGBoost and Random Forest using the scikit-learn library, and I have used tools such as pandas, numpy, and matplotlib for data visualization. Additionally, I have collaborated on the migration to AWS, where I have used cloud tools such as AWS SageMaker, S3, and EC2, and I have packaged locally developed code for execution in the cloud using Docker Compose.

Previously, I also worked at ST Analytics, but in a role that combined analysis and data science. I participated in the translation of an automatic valuation model from PL-SQL to Python, which allowed me to significantly improve the model's execution speed thanks to the multiprocessing library. I also performed database analysis to identify anomalies and developed code to resolve these issues using pandas and numpy, among other libraries.

Before this, I was at Cognodata as a data analyst, where my main task was to perform SQL queries on the Banco Santander customer database. In this position, I developed skills in SQL, as well as interacting directly with clients.