Senior Data Scientist @ IE University

June 2025 - Present

I lead the data science work at IE Insurance and Tech Lab.

• Built Discrete Lag Non-linear Models (DLNMs) and Relative Risk (RR) curves that support long-term decision-making, informing pricing and risk strategies for insurers.
• Built interactive visual dashboards (Flask, PythonAnywhere) that communicate climate risk to insurers and the public.
• Implemented Kolmogorov-Arnold Networks (KANs) for weather forecasting, improving prediction accuracy.

Highlight: Launching the IE Insurance and Tech Lab.

COO @ Canonical Green

Apr 2023 - Present

At Canonical Green, we offer data science-based solutions for the ecological transition of the Industry 4.0.

• Built and deployed data science solutions that enable maritime clients to optimize routes and reduce carbon emissions by up to 10%.
• Delivered technical presentations to investors and stakeholders, translating complex algorithms into business value.
• Secured €93K in funding by winning a competitive grant from Missions València 2030, with our project ranked top by the jury.

Highlight: Presented technology to the European Parliament, positioning the innovation for EU-wide adoption.

Data Scientist @ Komorebi AI

Sep 2022 - Apr 2023

I worked as a full-stack data scientist on projects for industrial clients, building models and decision tools that turned raw data into actionable insights.

• Cleaned and processed 500K+ data points from raw sensor data, enabling accurate fish population monitoring for overfishing prevention.
• Designed and deployed gradient-boosted and CNN models using scikit-learn that achieved 90%+ accuracy in real-time tuna detection.
• Built an interactive Streamlit dashboard that leadership used daily for operational decisions, reducing analysis time by 80%.

Predoctoral Research Staff @ University of Cádiz

Sep 2019 - Aug 2022

I contributed to multiple research projects with industrial partners, building machine learning solutions for real-world applications.

• Built machine learning models for Industry 4.0 applications in energy monitoring and sustainable fishing, reducing operational costs for industrial partners.
• Partnered with Spain's Health Alerts Centre to create COVID-19 ICU forecasting models that informed national policy decisions during the pandemic.
• Delivered presentations at international conferences, translating complex research into actionable insights for diverse audiences.
• Published 5 peer-reviewed papers in Q1/Q2 journals, advancing the field of applied machine learning and data science.

Junior Data Scientist @ Foqum

Jan 2019 - Jun 2019

This was my first professional experience, where I was introduced to collaborative work environments and machine learning project workflows.

• Built and tested neural network models using Keras and TensorFlow for non-intrusive load monitoring (NILM) to estimate appliance usage from aggregate power data.
• Contributed to energy disaggregation projects that helped optimize power consumption analysis.
• Learned industry best practices for version control, reproducibility, and presenting technical results.

Postdoctoral Researcher & Adjunct Professor @ IE University

Sep 2023 - Present

I contribute to research projects and teach programming courses, bridging academic research and practical education.

• Built climate impact models simulating insurance risk under SSP-RCP scenarios that VIG used for portfolio strategy.
• Implemented Kolmogorov-Arnold Networks (KANs) for weather forecasting, improving prediction accuracy.
• Designed optimization algorithms that reduce ship GHG emissions through real-time weather-based routing.
• Built and maintained IE Research Datalab's official website, increasing research visibility and collaboration opportunities.
• Delivered 4 courses (Computer Programming I, Coding Lab, Time Series Analysis, Applied Math Lab) to 100+ students with consistently high satisfaction ratings.

PhD in Computer Engineering @ University of Cádiz

Sep 2019 - Jul 2023

Thesis: "Applications of Machine Learning and Data Science to the Blue Economy" under the supervision of David Gómez-Ullate.

• Partnered with industrial clients in healthcare, energy, and marine transport to build applied ML solutions.
• Built machine learning models for Industry 4.0 applications in energy monitoring and sustainable fishing, reducing operational costs for industrial partners.
• Partnered with Spain's Health Alerts Centre to create COVID-19 ICU forecasting models that informed national policy decisions during the pandemic.
• Delivered presentations at international conferences, translating complex research into actionable insights for diverse audiences.
• Published 5 peer-reviewed papers in Q1/Q2 journals, advancing the field of applied machine learning and data science.

Highlights: Cum Laude distinction -- International awards in sustainability and computer vision -- COVID response research

MSc in Statistical and Computational Information Processing @ UPM

Sep 2018 - Jul 2019

I completed my master's degree specializing in data science, acquiring essential skills in data analysis, data mining, neural networks, and Big Data technologies.

Degree in Physics @ Complutense University of Madrid

Sep 2014 - Jul 2018

I completed my bachelor's degree in Physics, earning honors in four subjects related to Quantum Physics and Astrophysics. This foundation in rigorous analytical thinking prepared me for advanced work in data science and machine learning.