At Fundación ISEAK, I processed and analysed data from sources including INE, EUSTAT, Social Security and InfoJobs using R. I developed data preparation workflows and presented findings to clients and non-technical stakeholders.
I automated recurring data-processing and reporting workflows and built management tools using R, MS Office and AppleScript. My work also included financial analysis and forecasting for European and Basque Government-funded projects.
For my MSc thesis at Universidad Complutense de Madrid, I developed and evaluated fraud-classification models using the IEEE-CIS Fraud Detection dataset, with the final model achieving an AUC of 0.9444. I designed a cost-sensitive framework to prioritise transactions for manual review; at a $3 review cost, its selected elbow point generated $2.16M in net savings while reviewing 3.09% of transactions.
I used SHAP to interpret the model and FastAPI to deploy it, with Tableau supporting analytical decision-making. I hold an MSc in Data Science, Big Data & Business Analytics, alongside an MSc in Digital Marketing and a BSc in Business Administration & Management.
