Welcome
Statistics, mathematics, and AI with a rigorous applied perspective.
I have a double major in Mathematics and Physics from the University of Valladolid and a Master's in Statistics for Data Science from Carlos III University of Madrid. My background combines strong theoretical training with hands-on work in research, quantitative analysis, and machine learning-related applications.
Profile
About Me
My academic interests include probability, statistics, data science, operations research, computation, and applied mathematics. I am especially interested in deepening my expertise in statistics and artificial intelligence while working on analytically grounded, practical problems.
Statistics and Probability
Strong training in statistical tools, probabilistic thinking, and quantitative reasoning across both academic coursework and applied projects.
Data Science and AI
Experience with machine learning topics, deep learning coursework, and research directions connected to predictive modelling and intelligent systems.
Operations Research
Exposure to optimization and decision models, including thesis work on preference modelling and route choice applications.
Applied Mathematical Thinking
A foundation built through dual training in Mathematics and Physics, with an emphasis on rigor, abstraction, and real-world problem solving.
Curriculum
Education
Master's in Statistics for Data Science
Carlos III University of Madrid, Madrid
Final GPA: 9.55/10, with Honors in 36 ECTS. Final thesis on a two-level Plackett-Luce model for preference modelling in route choice.
Bachelor's in Mathematics
University of Valladolid, Valladolid
Final GPA: 9.365/10, Honors in 117 ECTS, ranked first in the graduating class, with Erasmus studies at the University of Perugia.
Bachelor's in Physics
University of Valladolid, Valladolid
Final GPA: 8.998/10, Honors in 108 ECTS, ranked second in the graduating class. Thesis on variational quantum algorithms.
Experience
Experience and Highlights
Research Fellowship at ICMAT
Research collaboration in the Department of Statistics and Operations Research through the JAE Intro ICU 2024 scholarship. Worked on preference modelling for shared transportation systems and predictive models for a social logging system.
Quantitative Finance Analyst Intern at AFI
Internship in Madrid during June to August 2023, combining advanced Excel, Python automation, and quantitative finance concepts such as Markov processes and Brownian motion for product valuation.
Courses, Congresses and Recognition
Presented thesis work at SEIO Lleida 2025, completed advanced courses in Deep Learning and Bayesian Time Series Analysis, and received distinctions including a silver medal at the National Physics Olympiad.
Technical Skills
Python, R, C/C++, VBA, MATLAB, Microsoft Excel, Linux terminal, LaTeX and GitHub.
Languages
Spanish, English (C1 CAE), French (DELF B2), and Italian (B1).