Lourdes Orvañanos
About Lourdes Orvañanos
Lourdes Orvañanos is a Senior Data Analytics and Software Integration Specialist at Vesta, with a strong educational background in data science and analytics from institutions like Google and Texas McCombs School of Business. She has extensive experience in data analysis, software development, and project management across various companies in Mexico and the United States.
Work at Vesta
Lourdes Orvañanos currently serves as a Senior Data Analytics and Software Integration Specialist at Vesta. She has been with the company since 2021, working in a hybrid capacity from Lake Oswego, Oregon. In her role, she applies her expertise in data analytics and software integration to deliver analytical insights and manage data pipelines. She also leads clients through technical implementations and integrations, ensuring successful project outcomes.
Education and Expertise
Lourdes Orvañanos has a strong educational background in data analytics and related fields. She earned a Master's degree in e-Commerce from Tecnológico de Monterrey, where she studied from 2003 to 2006. Additionally, she completed a Postgraduate program in Data Science and Business Analytics at Texas McCombs School of Business in 2023. She also holds a Google Data Analytics Professional Certificate, achieved in 2021. Her studies in Artificial Intelligence at Infocom - Université Lille 3 further enhance her analytical skills.
Professional Background
Lourdes Orvañanos has a diverse professional background in data analytics and software development. She began her career as a Data Analyst at HP in Guadalajara, Mexico, from 2003 to 2004. She then worked at IHG Hotels & Resorts as an IT Project Manager for seven years. After that, she held positions at STI Consultores and Industrias Dalmau, where she focused on software development and data analysis. Her experience spans over two decades, contributing to her expertise in the field.
Technical Skills and Projects
Lourdes Orvañanos has developed advanced technical skills in data analytics and machine learning. She has applied classification techniques such as k-Nearest Neighbors and hierarchical clustering for data categorization and risk assessment. Additionally, she has created predictive models using XGBoost, Decision Trees, and Random Forests for forecasting and fraud prevention. Her proficiency in SQL, Python, and Power BI enables her to craft impactful data visualizations and reporting tools.