
Gladys Choque Ulloa
Doctoral Student in Computer Science | Master’s in Statistics | Lic. in Statistics | Data Scientist | Research | Machine Learning | Deep Learning | WIDS Ambassador | Founder of Women in DataLab | LinkedIn Top Voice
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About
I’m Gladys Choque Ulloa, a Doctoral student in Computer Science at São Paulo University (USP), with a Master’s degree in Statistics from the Federal University of Rio Grande do Sul (UFRGS), Brazil and Graduated in Statistics from the National University of San Antonio Abad of Cusco, Peru. I am a Data Scientist, lecturer, mentor, teacher, speaker, and researcher with over 5 years of experience in both the academic and industrial sectors, leading data-driven projects and mentoring data science professionals and students in Latin America. I’m passionate about applying advanced statistical modeling, machine learning, deep learning, and time series forecasting techniques to transform data into actionable and high-impact insights across various industries including health, mining, and business intelligence. ✅ Technical Skills & Experience: 🔸Programming: R, Python, SQL. 🔸Data Analysis, Visualization, and Statistical Modeling. 🔸Applied Mathematics for Data Science. 🔸Time Series Forecasting Models and Predictive Analytics. 🔸Machine Learning & Deep Learning (Neural Networks). 🔸Computational Statistics and Big Data Analytics. ✅ Awards & Recognitions: 🔸 Winner at the MIT internacional Hackathon (2020). 🔸 Winner of the Clean Water Science Network Research Program at the University of Texas at Austin, USA. 🔸 Winner of the Science Club-Brazil program. 🔸 NASA Space Apps Hackathon 2020. 🔸 Named Outstanding Woman in Data and Data Science by Globant. 🔸 Recognized as a Top Voice in Data Science by LinkedIn. 🔸 Creator of the data science content brand “Datos con Gladys”. 🔸 Founder of the Women in DataLab community. I actively participate as a mentor, lecturer, public speaker, and community leader, contributing to national and international events, conferences, workshops, and mentoring programs for aspiring data scientists and statisticians, with a clear focus on female empowerment in STEM.
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