Jose Luis Garcia Tucci
MSc in Data Science (UOC, 2025) and Senior Electrical Engineer with 15+ years of experience delivering high-voltage substations, renewables, and industrial energy projects (HV/MV/LV) across oil & gas, petrochemical, and power systems. Strong focus on data analytics, machine learning, predictive modeling, data visualization, and geospatial analysis, bridging engineering domain expertise with modern data-driven decision-making. Proficient in Python, R, SQL, and BI tools (Power BI / Tableau) to turn complex technical and market/operational data into actionable insights.
Technical Skills: Python, R, SQL, Java, Bash, C# | Pandas, Scikit-learn, PyTorch, TensorFlow | Power BI, Tableau, GIS (QGIS/Leaflet) | AWS, Docker | Git/GitHub
| MSc. Data Science | UOC - Universitat Oberta de Catalunya (2025) | |
| Specialization - IBM - AI Developer Professional Certificate | IBM – Coursera (2025) | Link |
| Microsoft Power BI Data Analyst | Microsoft – Coursera (2024) | Link |
| Software Engineering Essentials | IBM – Coursera (2024) | Link |
| Google Data Analytics Professional Certificate | Google – Coursera (2022) | Link |
| Specialization - Applied Data Science with Python | University of Michigan – Coursera (2022) | Link |
| Master Electrical Engineering – Industrial Installations | Universitat Politècnica de Catalunya (2013) | |
| B.S. Electrical Engineering – Power Systems | Universidad Central de Venezuela (2011) |
Lead Discipline Engineer, Technip Energies (Barcelona) (2022 – Present)
- Lead electrical discipline for major energy and industrial projects, including a 400 MW Green Hydrogen plant.
- Coordinate multidisciplinary teams of engineers and designers across multiple projects and stakeholders.
- Developed automated ETL pipelines for electrical infrastructure analytics and reporting.
- Built and maintained Power BI dashboards to support data management, performance tracking, and decision-making.
Lead Engineer – Electrical Component, GE Renewable Energy (2017 – 2022)
- Led electrical engineering teams for global wind farm projects and tower internals design execution.
- Supported engineering quality processes and continuous improvement (e.g., DFMEA / 8D) to improve delivery performance.
- Developed data visualization tools to support energy efficiency monitoring and engineering reporting.
Associate Professor, Universidad Central de Venezuela (2012 – 2013)
- Taught Power Plants and Substations (8th-semester electrical engineering).
- Delivered content on HV substations, outage factor, surge arresters, grounding design, and systems modeling.
Web Trekking APP (Mapping APP for GPX route visualization and creation)
Web APP Madrid Air Quality (R deployed in Shinyapps)
Barcelona Rent Prices by Metro Station (R + Leaflet / Shiny)
Weather Analysis (Python)
Classification Model - Cancer diagnostic Dataset (R)
Jump2Digital Hackathon
Deep Learning for Fault Detection in 3 Phase Induction Motors (BRB Fault Detector)
- Developed and deployed a CNN app to diagnose broken rotor bars from stator current signals using GASF encoding and deep learning.
- Live demo (Hugging Face Space): BRB Fault Detector
- 📄 Related publication (MDPI / Sciforum): https://sciforum.net/paper/view/28130
- Learning Path - Become a Python Developer – LinkedIn Learning - Completed Oct-2019
- Learning Path - Advance Your Skills in Python – LinkedIn Learning - Completed Sept-2019
- Learning Path - Become a Data Scientist – LinkedIn Learning - Completed Feb-2022
- Course – Learning Java – LinkedIn Learning - Completed Mar-2022
- Course – Docker for Data Scientist – LinkedIn Learning - Completed May-2022
- Skill Path - Analyze Data with SQL – Codecademy - Completed May-2022
- Course – Introduction to NoSQL Databases with MongoDB – Coursera – Completed Jun-2022
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Garcia Tucci, J.; Burriel-Valencia, J.; Sapena-Bañó; Martínez-Román, J.; Barrera, K.
Non-invasive diagnosis of broken rotor bars in induction motors using deep learning and GASF representations.
Proceedings of the 6th International Electronic Conference on Applied Sciences, 9–11 December 2025, MDPI: Basel, Switzerland.
🔗 https://sciforum.net/paper/view/28130 -
Jose Luis Garcia Tucci.
Diagnóstico de fallas por rotura de barras en motores de inducción trifásicos mediante el uso de modelos de deep learning.
Master’s Thesis, Universitat Oberta de Catalunya (UOC), 2025.
🔗 https://openaccess.uoc.edu/items/db3c1785-c06d-419d-b7f4-2b17f8b3a4ee -
Jose Luis Garcia Tucci. “Churn rate visualizations in Python”, Medium.com
🔗 https://medium.com/@jlgarciatucci/churn-rate-visualizations-in-python-3016602633da
- Boehringer Ingelheim Hackathon 2024 (NUWE) - Top Ten Finalist
- Jump2Digital Hackathon 2023 (Data Science & AI) - Finalist
- AWS DeepRacer 2022 - Top 10% Rank (61/4197)