Denisse Mejorado
AI Architect at Oracle
Mexico City
Summary
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Senior🎓
Top SchoolDenisse Mejorado is an AI Architect with a decade of experience blending data science, engineering, and domain expertise across finance, healthcare, videogames, and public policy. An economist by training with an M.S. in Data Science and ongoing PhD research at Stevens Institute of Technology, she builds end-to-end ML pipelines, scalable AI infrastructures, and network-driven analytic systems that surface strategic, operational insights. She has led teams to productionize models and data products—most recently architecting client-facing AI solutions at Oracle and previously managing a 7-person data organization at Johnson & Johnson that delivered salesforce-targeting and competitive-penalty models. Her research and applied work often combine NLP, graph analytics, and visual analytics to reveal hidden patterns in competitive and organizational behavior, a capability she has used from forecasting player actions in games to mapping systems engineering research trends. Based in Mexico City, she pairs rigorous academic methods with hands-on implementation in PySpark, Scikit-Learn and TensorFlow to move projects from prototype to production.
10 years of coding experience
13 years of employment as a software developer
Bachelor's degree Economics, Bachelor's degree Economics at Universidad Autónoma de Nuevo LeónDoctor of Philosophy - PhD Engineering/Industrial Management Data Science, Doctor of Philosophy - PhD Engineering/Industrial Management Data Science at Stevens Institute of TechnologyM.S. in Data Science Data Science, M.S. in Data Science Data Science at Instituto Tecnológico Autónomo de México
English, SpanishGithub contributions (5)
DennyMtz/TDA_proyectos
Apr 2016 - Jun 2016
Contributions:1 PR, 3 pushes, 1 branch in 2 months
clasedatospythonproyectos
DennyMtz/DPA_Ecobici
Apr 2016 - Jun 2016
Contributions:8 pushes, 1 branch in 2 months
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