Greater Madrid Metropolitan Area
While portraying a scientific career in Astrophysics, my interests have been focused towards the application of Data Science and Artifical Intelligence to solving scientific problems. I have great experience with Machine Learning and Deep Learning tools using Python and I am very interested in advanced ML methods to leverage model results. I excel on applying diverse methods to make ML models more interpretable, from model agnostic explainability methods to the extraction of KPIs to guide the final user on making informed decisions based on model predictions. I have experience working on a variety of fields, currently working on a project for the early diagnosis and prognosis of diseases with high prevalence on the aged population. I have a huge interest in R&D of new technologies, specially if they are oriented towards the transition to a more sustainable, environmentally respectful world.
Data Scientist focused in the development and implementation of Machine Learning and Deep Learning Models for the analysis of TimeSeries data, from classification to forecasting. Great experience applying explainability techniques to ML models. Participation in a variety of projects: - Research of AI solutions for the treatment and prevention of diseases related to aging. - Discovery and implementation of of AI powered indicators for decision making for a project in the Energy sector. - Implementation of TimeSeries forecasting methods for e-commerce sales predictions for a company in the Pharma sector.
Profesora de la asignatura de "Bases de datos de nueva generación" del Master Universitario en Análisis de Datos Masivos (Big Data) en su modalidad online.
Research in high energy astrophysics within the CTA and MAGIC observatories. Software developing for new Cherenkov telescopes, application of deep learning techniques to data analysis.