I am a data scientist with strong technical skills and an academic background in engineering, optimization, and machine learning. As a member of CIRRELT, one of the worldwide leading research centers in optimization, my focus is on large-scale and stochastic optimization for logistic systems and other real-life applications. I hold a bachelor's degree in Computer Science from the Technological University of Pereira (2014), a master's degree in Electrical Engineering with an emphasis on Operational Research (2016) and I am currently finishing my Ph.D. studies in Computer Science at the University of Montréal. Since my undergraduate studies, I have been the recipient of multiple interdisciplinary awards, including scholarships and internship funding in Canada, Europe, and South America. My passion lies in solving real-life problems with tailored data and algorithms to deliver high-performing AI solutions. A large part of my graduate-level work has been devoted to the research and application of optimization and artificial intelligence in collaboration with a wide variety of professionals across America, Europe, and Asia. This has enabled us to present managerial and methodological insights at scientific conferences and aim to publish in quality journals. With over seven years of commercial software development experience, I have a strong emphasis on applied research. My research interests span across multiple disciplines in operational research, including logistics, vehicle routing, and data science, among others. The main focus of my research is the development of mathematical programming tools and heuristic methods for the solution of hard combinatorial problems with uncertainty arising in those areas.Proficient: C++, Java, Julia, Ruby, Python (docplex, pyomo, scikit-learn, NumPy, SciPy, pandas), TensorFlow, Keras, Pytorch, CPLEX, Gurobi, OpenCV, OpenMP, CUDA, LaTex, Excel.Knowledgeable: SQL, R, Spark (Spark SQL, MLLib, Pyspark), Xpress, Knitro, Tableau, PowerBI.