Hi! I am a Mathematics and Computer Science graduate with industry and research experience with data science and software engineering in various domains. My interests include machine learning engineering, MLOps, interpretable and interactive ML, data visualization, data science and its applications.

At New York University Abu Dhabi, I worked at the Music and Sound Cultures (MaSC) research group on computational audio analysis, using machine learning and visualization techniques to explore similarities and interactions between music from different regions. I also worked at the Visualization and Data Analytics Research Center (ViDA) on interactive visualization methods for counterfactual explanations for machine learning models. As a researcher at Quantil, I worked on projects related to crime prediction models and their interpretation, domestic violence, and credit scoring. At Duke I worked on explanation methods for data-driven systems using causal inference and as a consultant developing machine learning models to predict property values for a proptech startup.

At Scotiabank I worked as a Cloud and Software Engineer using both Azure and Google Cloud. I migrated credit scoring systems from batch to real-time inference and deployed multimodal deep learning models using MLOps best practices on GCP as a Machine Learning Engineer at Quipu. Currently, as a Senior Machine Learning Engineer at Nubank, I lead the ML infrastructure for lending expansion into Mexico and Colombia, building scalable pipelines for real-time risk models and establishing comprehensive monitoring frameworks.