Acerca de Francisco José
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Competencia profesional básica
Experiencia
- Cabildo of La PalmaData ScientistINTERNET DE LAS COSASenero de 2024 - enero de 2025 (1 año)Santa Cruz de La Palma, España• Led EDA using Python (Pandas, Matplotlib, Seaborn) and R (ggplot2, dplyr) across 5+ datasets (mobility, night sky, meteorology, air quality). Found ~0.6 Pearson correlation between CO₂ and tidal cycles, suggesting gas buildup tied to tides. This led the Emergency Dept. to revise coastal safety protocols post-eruption.• Created dashboards in Power BI and Tableau for Waste Management and HR. The HR dashboard segmented 1,000+ employees by role and department. The waste dashboard showed recycling unit growth linked to more paper, glass, and packaging collected, justifying changes in the annual report.• Built real-time dashboards in ArcGIS Online, including mobility (vehicles/pedestrians) and a digital twin for CO₂ in Puerto Naos. The Emergency Dept. uses the CO₂ dashboard daily for habitability checks, while others serve internal analytics.• Cleaned and integrated a legacy dataset (3M+ records) into the Cabildo’s meteorological portal. Fixed format issues and created metrics like thermal sensation. Extended public archive from 2022 back to 2016, supporting long-term climate analysis and dashboards.• Proposed a PostgreSQL schema for CO₂ sensor tracking. Automated alias creation from address initials and linked installer/ownership data from private forms to public tables. Ensured consistent, centralized data access for future deployments.
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Formación
- MSc in Data ScienceOpen University of Catalonia (UOC)2025Master’s Thesis: Developed a sales forecasting and audience segmentation system for Filarmonía de Madrid using real ticketing data, applying machine learning models (Random Forest, CNN’s, RNN’s, ARIMA), clustering techniques (K-Means, DBSCAN), and RFM analysis, while integrating external event data and addressing overfitting through cross-validation and hyperparameter tuning.
- BSc in PhysicsUniversity of La Laguna (ULL)2021Bachelor’s Thesis: Analyzed the intrinsic properties of the EMIR instrument (GTC, IAC) through image-based photometric calibration, using Python scripts to extract parameters such as linearity, gain, and sensor drift under varying conditions, and documenting results following scientific standards with LaTeX.