Senior Data Scientist & Technical Lead @ IE University × Vienna Insurance Group

June 2025 - Present | Madrid, Spain

Client: Vienna Insurance Group

I work on climate risk data science at IE Insurance and Tech Lab, drawing on methods from ML, statistics, and climate science to address real insurance problems.

• Lead client-facing technical delivery for Vienna Insurance Group collaboration, managing stakeholder presentations, steering committee communications, and project roadmap coordination with international insurance executives.
• Present research findings directly to VIG executive leadership and cross-functional teams, translating complex climate models into actionable insurance risk insights for portfolio analysis.
• Deployed interactive Flask web application (hosted on PythonAnywhere) for climate mortality risk visualization, enabling real-time exploration of SSP-RCP scenarios by insurance analysts and public stakeholders.
• Built production-grade climate risk models using DLNMs and Relative Risk curves, integrating weather data, mortality statistics, and insurance portfolio analysis for quantitative risk assessment.
• Established CI/CD workflows and pre-commit hooks for data pipeline quality control, ensuring reproducible research outputs and streamlined client deliverables.
• Leveraged GenAI tools (Claude, OpenAI, Gemini via OpenCode) for research acceleration, automated code generation, and multi-agent workflows.

Highlight: Presented research at ICMS Climate Change and Insurance 2025 workshop in Edinburgh to actuaries, climate scientists, and industry representatives.

COO & Technical Lead @ Canonical Green

April 2023 - Present | Madrid, Spain

• Built and deployed route optimization models for maritime clients, targeting reductions in fuel use and carbon emissions of up to 40% through weather-integrated navigation algorithms.
• Managed data workflows using AWS S3 for large-scale climate dataset storage and retrieval.
• Led technical presentations to diverse audiences including investors, funding juries, institutional stakeholders, and the general public, adapting technical content for each setting.
• Showcased the project at Prototypes for Humanity 2024 in Dubai, selected among 100 innovations from over 2,000 global submissions.
• Invited to present technology at the European Parliament as one of top 5 ecological transition solutions in Europe.
• Featured on The Conversation Weekly podcast discussing maritime decarbonization for international audience.
• Secured €93K in competitive funding from Missions València 2030, with project ranked #1 by evaluation jury.
• Utilized LLM-powered tools for technical documentation and presentation generation, streamlining stakeholder communication.

Data Scientist @ Komorebi AI

September 2022 - April 2023 | Madrid, Spain

• Built end-to-end data pipelines processing 500K+ sensor data points from raw inputs to production-ready ML models for industrial fish monitoring.
• Designed and deployed gradient-boosted and CNN models achieving 90%+ accuracy in real-time tuna detection for overfishing prevention.
• Developed interactive Streamlit dashboard used daily by operations team for decision-making.
• Collaborated with Satlink (industrial client) to translate business requirements into technical ML solutions.
• Implemented Git workflows with version control and code reviews for team collaboration on production codebase.

Predoctoral Research Staff @ University of Cádiz

Sep 2019 - Aug 2022

I contributed to multiple research projects with industrial partners, building machine learning solutions for applied problems.

• Developed machine learning models for Industry 4.0 applications in energy monitoring and sustainable fishing, in collaboration with industrial partners.
• Collaborated with Spain's Health Alerts Centre to develop COVID-19 ICU forecasting models used to support national policy decisions during the pandemic.
• Presented research at international conferences to technical and mixed audiences.
• Published 5 peer-reviewed papers in Q1/Q2 journals on applied machine learning and data science.

Junior Data Scientist @ Foqum

January 2019 - June 2019 | Madrid, Spain

• Built neural network models using Keras and TensorFlow for NILM (Non-Intrusive Load Monitoring) to estimate appliance usage from aggregate power data.
• Contributed to energy disaggregation projects optimizing power consumption analysis for energy sector clients.
• Adopted professional Git workflows and reproducibility practices for production ML systems.

Postdoctoral Researcher & Adjunct Professor @ IE University

September 2023 - Present | Madrid and Segovia, Spain

Lead applied research on cutting-edge machine learning architectures and climate modeling, while teaching technical courses to diverse student audiences.

• Implemented Kolmogorov-Arnold Networks (KANs) for weather forecasting, applying a novel neural architecture (published 2024) to meteorological time series.
• Developed optimization algorithms for weather-based maritime routing, integrating meteorological data with route planning to reduce GHG emissions in shipping industry.
• Presented research at the ICMS Climate Change and Insurance 2025 workshop in Edinburgh to an international audience of actuaries, climate scientists, and industry practitioners.
• Delivered 4 technical courses to 100+ students (Computer Programming I, Coding Lab, Time Series Analysis, Applied Math Lab), translating complex programming and statistics concepts for undergraduate audiences.
• Built and maintained IE Research Datalab's official website, improving research group visibility and communication of technical projects to broader audiences.
• Mentored undergraduate researchers on data science projects, developing curriculum materials and guiding student development in Python, ML frameworks, and research methodologies.

Teaching philosophy: Technical education is about bridging the gap between complex concepts and practical understanding; the same skill needed for client-facing technical consulting.

PhD in Computer Engineering @ University of Cádiz

September 2019 - July 2023 | Cádiz, Spain

Thesis: "Applications of Machine Learning and Data Science to the Blue Economy" (Cum Laude)

• Collaborated with industrial clients in healthcare, energy, and maritime transport to build applied ML solutions.
• Developed computer vision system (NeoCam) for neonatal monitoring that won 2nd prize in OpenCV AI Competition 2021 (1,400+ teams).
• Built COVID-19 ICU forecasting models in collaboration with Spain's Health Alerts Centre, supporting national policy decisions during pandemic.
• Published 5 papers in Q1/Q2 journals on applied machine learning and data science.
• Developed automated data pipelines in Python/R from raw data ingestion to production-ready research outputs.

MSc in Statistical and Computational Information Processing @ UPM

September 2018 - July 2019 | Madrid, Spain

Specialization in data science, machine learning, and big data technologies.

Degree in Physics @ Complutense University of Madrid

September 2014 - July 2018 | Madrid, Spain

Honors in Quantum Physics and Astrophysics. Foundation in rigorous analytical thinking.