CV

Data Scientist Trainee

Jakala Iberia

Summer Internship

Astrophysics, University of Oxford

• Absorbed the astronomical and dynamical background involved in the interpretation of data from ESA’s Gaia mission.
• Learnt C++ and Python programming languages to use standard tools for the management, analysis and visualization of data.
• Analyzed both spatial coordinates and proper motions from RR Lyrae stars throughout the galaxy.
• Developed the first steps towards a new dynamical model of the population of RR Lyrae stars.

510 Species Classification

• CNN that classifies 510 bird species with an accuracy of 0.93.

XGBoost for car pricing

• Machine learning model that predicts car prices with an R2 score of 0.92.

Song Recommender

• Conceived by clustering over 60.000 songs with similar audio features.

Financial fraud detector

• Developed three machine learning models that detect up to 99% of fraudulent transactions with both high recall and precision.

Traffic & Air Quality study

• Analyzed the correlation between air quality and traffic flow in Madrid.

Data Analytics Bootcamp

IronHack

• Data Analysis using Python (Pandas, NumPy) & MySQL.
• Data Visualization (Tableau, Plotly & Seaborn).
• Build, Evaluate & Deploy ML Models and Pipelines (Scikit-learn).
• Inferential Statistics in Python & Business Intelligence.
• Data Wrangling, Data Cleaning, API & Web Scraping.

Bachelor's Degree in Physics (3/4 years completed)

University of Seville

• Linear Algebra & Geometry
• Mathematical Analysis
• Scientific Programming
• Numerical Methods & Simulation
• Mathematical methods I & II.
  • Probability and Statistics.
  • Complex analysis.
  • Resolution methods of an ODE & PDES.
• Quantum mechanics, Electromagnetism, Classical Mechanics, Thermodynamics, Statistical Mechanics, Chemistry, Classical Electrodynamics, Electric Circuits & Instrumentation and Optics.