About
My Data Odyssey: A Stochastic Voyage
My data journey started back in the mid 2000s, working as a Reliability Engineer of Power Systems for the operator of the world’s fourth biggest hydroelectric power plant Guri. The objective was ambitious:
- Dynamic monitoring of the risk of blackouts with probabilistic KPIs.
At that time the position Data Scientist didn’t exist, but some books in the realm of Data Mining and Emerging Computing Methods trying to organise and formalise the field. However, the area of Survival Analysis, specifically Reliability and Risk were pretty matured due to their importance in the industry.
Going forward with a stochastic thinking in an organisation with a lack of statistical culture and less amounts of data wasn’t easy, relying only on a mixture of internal ERP data, world surveys and standards. A continuous push towards a data culture from top-level management was key, and it still is!
Education
IBM
IBM AI Engineering Professional Certificate, 2022-2023 (Joseph Santarcangelo et al.)
Udacity
AI for Business Leaders, Nanodegree, 2022 (William Ross & Luis Serrano)
Introduction to Machine Learning Free Course, 2017 (Sebastian Thrun & Katie Malone)
Stanford University
STATSX0001 Online: Statistical Learning, 2022 (Trevor Hastie & Robert Tibshirani)
Udemy
100 Days of Code: The Complete Python Pro Bootcamp for 20231 (Angela Yu)
Microsoft Power BI Desktop for Business Intelligence, 2022 (Maven Analytics, Chris Dutton)
Tableau A-Z: Hands-On Tableau Training for Data Science, 2019 (Kirill Eremenko)
Kaggle
Feature Engineering, 2023 (Ryan Holbrook & Alexis Cook)
University of Nottingham
MSc. Electrical Technology for Sustainable and Renewable Energy Systems, UK (2010-2011)
Universidad del Zulia
Dipl.-Ing. Electrical Engineering, VE (2000-2006)
Languages
- Spanish (Native Language)
- English (Fluent)
- German (Fluent)
Publications
To date I’ve authored and co-authored several publications2 related to advanced analyitcs in different domains like Power & Energy Systems, IoT and utilities.