Alexey David Velasquez Betancurt

Machine Learning Engineer and Data Scientist with experience designing and deploying end-to-end ML and NLP systems for real-world decision-making and applied research. Specialized in Transformer-based models (BERT), sentiment analysis, pattern recognition, and anomaly detection, with a strong focus on model interpretability and performance optimization. Proven track record building production-ready pipelines, integrating machine learning models with business systems, and delivering real-time analytics through automated workflows and data visualization platforms. Experienced in evaluating and benchmarking multiple algorithms including LightGBM, Random Forest, Support Vector Machines, Autoencoders, and neural networks to select optimal solutions based on data and use-case constraints. Background in applied research and academic mentorship, including the development of explainable AI solutions using SHAP to replicate and improve expert decision-making in high-impact domains. Holds a Master’s in Engineering with a focus on Machine Learning and combines strong theoretical foundations with practical, results-driven implementation.