Hello, I'm Gabriela Espinoza.
I'm very passionate about art, technolgy, learning and shareInterdisciplinary professional with expertise in economics, tech, data science, and data analytics,I am passionate about using data to drive innovation and solve complex problems. I have a strong foundation in data visualization, statistical analysis, SQL, Python, R, UI/UX.
My experiences is very wide in consulting, education, e learning, tech companies, government organizations and NGO's have allowed me to develop a unique set of skills. I hold a Master's degree in Information Technology, I apply machine learning to my thesis master degree studied gender gap in STEM carrers. I have also been responsible for creating and documenting public statistics, as well as designing statistical analyses on large data sets using R and Python programming languages. I have served as a mentor in the technology field for people with disabilities, and have taught digital design and data analysis to students in non-profit organizations. I am excited to bring my skills and experiences to new opportunities, and am always looking for ways to grow and learn in my field.
Thesis on low female participation in STEM careers, applying machine learning techniques.Note: 10
Pending thesis
Thesis on the impact of the quality of secondary education, public or private, on the performance of university students. I made statistical models to analyze the difference in the final math grades taking into account variables such as: gender, type of public or private school, type of career, etc. Research helped to promote public policy decisions within the University of Costa Rica, in order to reduce a possible social gap
As a Lead Researcher and Professor at LADAINA (Laboratorio Datalogico Nacional), I oversee research projects in NLP, web scraping, and text analytics, analyzing large-scale media and industry data. My work includes leading key research initiatives on media analysis, STEAM career mapping in Costa Rica, and gentrification trends, while managing and mentoring a six-person research team. Additionally, I contribute to academic publications that bridge research, industry, and policy-making, driving data-driven decision-making in various fields.I also serve as a Professor of Data Mining in the Master's Program, where I teach advanced techniques in data extraction, transformation, and machine learning applications.
As a Senior Data Scientist at Accenture, working in Google Cloud Marketing Data Science, I leverage a variety of Google Cloud tools, including Python, BigQuery, Plex, Taskflow, and Buganizer. I also collaborate with cross-functional teams to ensure that data models and analyses align with business objectives, contributing to impactful marketing decisions.
As a Data Analyst leader, I was responsible for designing and creating comprehensive public statistical reports, as well as designing and implementing statistical analysis on large datasets. I worked with data of the national public number 144 in Argentina, it's an operating nationwide line 144 which provides information, guidance, advice, and support to women in situations of violence 365 days a year, 24 hours a day, free of charge. My expertise included text mining, machine learning, and data analysis techniques using R and Python and SQL. I was highly motivated and dedicated to using my skills to make a positive impact in this role. I successfully contributed to migrate large historical datasets to a national consulting system and interpreted the data to identify key trends and inform decision-making. I also have extensive experience in managing large-scale data migration projects, implementing efficient architecture and processes, and utilizing my expertise in text mining, machine learning, and data analysis to drive success.
I conducted research on a variety of topics including population, gender, employment, income, and development using Python, SQL, and R. I worked with a large amount of data and used data science methods such as megadata extraction, database generation, data quality analysis, data visualization, data modeling, statistical analysis, and benchmarking to conduct quarterly analysis of the Permanent Household Survey (EPH). My expertise included data analytics and data science, and I was skilled at making projections based on my findings. I was committed to producing high-quality research and making a positive impact on policy and decision-making
