Executive profile
Carlos is a Senior Data Scientist and Mechanical Engineer with more than 10 years of experience in industrial analytics, energy systems, operational optimization, energy efficiency, and machine learning. He specializes in high-frequency time-series analysis, anomaly detection, root-cause analysis, forecasting, explainable AI, and production-oriented machine learning workflows.
He holds postgraduate degrees in Applied Statistics and Energy Management and is currently a Master of Mathematics Candidate at Universidad del Norte. His professional training also includes Industrial Energy Efficiency through the International Energy Agency in São Paulo, Brazil.
Current focus:Artificial IntelligenceMachine LearningOperational AnalyticsIndustrial Data ScienceProduct Architecture
Education
Mechanical Engineering
Universidad del Atlántico · Colombia
Applied Statistics Postgraduate Degree
Universidad del Atlántico · Colombia
Energy Management Postgraduate Degree
Universidad del Atlántico · Colombia
Master of Mathematics Candidate
Universidad del Norte · Colombia
Professional Training
Industrial Energy Efficiency
International Energy Agency · São Paulo, Brazil
Professional experience
Across industrial analytics, machine learning, and energy systems.
Industrial Analytics
Machine Learning
Energy Systems
Operational Optimization
Explainable AI
Forecasting
Professional Impact
Selected achievements from Carlos Camargo’s professional career prior to OPERION.
Energy Efficiency & Industrial Analytics
Colombia’s largest energy company
Designed and implemented an upstream energy-efficiency and analytics program that, over four years, optimized total energy demand by approximately 10%, generated approximately USD 56 million in savings, and reduced greenhouse gas emissions by more than 700,000 tCO₂e.
Energy Portfolio Forecasting
Developed energy-demand forecasting models to support the planning and management of an energy contract portfolio valued at approximately USD 800 million.
AI-Enabled Operational Analytics
Led the implementation of an AI-enabled analytics platform for energy-performance monitoring, anomaly detection, and data-quality improvement, generating nearly USD 1 million in incremental savings.