I’m a data scientist based in Madrid. I am pasionate about artificial intelligence, information visualization, digital tranformation and economics. Recently graduated with a bachelor's degree in Computer Science and Engineering. Experience in both research and consulting.
Served as a technological consultant, developing data-driven projects, optimizing data pipelines and processing large datasets. Developed and deployed machine learning models to enhance business outcomes. Integrated AI models into production, collaborating with cross-functional teams to improve decision-making and operational efficiency.
Collaborated with 12 de Octubre University Hospital to analyze actigraphy data from head-injured patients. Responsibilities included extensive data cleaning, data analysis and visualization, and training classification models to identify head trauma through actigraphy analysis.
Relevant coursework: Statistics, Machine learning, Artificial intelligence in business, Data architecture, Files and databases, Genetic algorithms.
Final Thesis: "Analysis of Actigraphy Data to Identify Sleep Disorders". Earned a score of 9.8 out of 10 for the quality and rigor of the research.
A simple wrapper around LangChain to obtain structured outputs from a locally run LLM. Bond allows users to extract structured information from textual input based on a provided format.
A web-based application designed to transform user prompts into custom diagrams. It does so by leveraging the power of local Large Language Models (LLMs) through Ollama.
A rapid note-taking tool powered by locally run LLMs. Brain Notes ensures correct grammar and coherence in notes, even if the user's input is incomplete, allowing for efficient and seamless note-taking experiences.
Data analysis to uncover key insights and optimization opportunities. This project secured my team the first place at the Madrid Engineering Week Datathon.
Developed a machine learning model with NLP and text mining to predict salaries based on job titles and descriptions.
Developed a deep learn ing model to forecast employee departures, by analyzing workforce data to uncover patterns leading to departures.
Designed and implemented a MongoDB-based NoSQL database for artist, concert, and recording data, then optimized the system with a cluster design and developed data pipelines for migration from legacy databases.
Designed and implemented an SQL database for a hospital management system and conducted performance analyses across various use cases to identify and propose optimizations.
Leveraged advanced machine learning techniques to optimize solar panel efficiency by analyzing climatic data and developing predictive weather models.
Designed and implemented an expert system to recommend vehicles for specific target markets, creating adaptive models to analyze customer preferences and vehicle features.
Conducted a detailed data analysis and visualization project to identify factors influencing high blood pressure.
Analyzed and visualized the range of computer science courses available on a selected website, using data analytics to assess course diversity, focus areas, and accessibility.