Maria聽Gaska
CTO at Instituto Humai
Greater Buenos Aires Argentina
Summary
馃懁
Senior馃帗
Top SchoolMaria Gaska is a technology leader and machine learning engineer with 11 years of experience who currently serves as CTO at Instituto Humai while leading AI product work as Head of Artificial Intelligence at Vetted. With a background in Economics (Magna Cum Laude) and a master's in data mining, she blends rigorous analytical thinking with hands-on ML and cloud engineering, holding AWS Solutions Architect certification. Her career spans applied AI roles at AWS, public-sector data science for Buenos Aires, and speech recognition and teaching positions, evidencing strength in both research and production. She champions ethical, socially impactful AI, technological sovereignty, open source and gender equality, and has contributed practical educational ML materials鈥攕uch as agricultural data analysis exercises鈥攆or Humai鈥檚 public Python courses. Notably, she builds large-language-model driven search engines to rewire commerce toward transparency and customer-first recommendations.
11 years of coding experience
7 years of employment as a software developer
Maestr铆a Explotaci贸n de Datos y Descubrimiento del Conocimiento, Maestr铆a Explotaci贸n de Datos y Descubrimiento del Conocimiento at Facultad de Ciencias Exactas y NaturalesLicenciatura Magna Cum Laude econ贸micas, Licenciatura Magna Cum Laude econ贸micas at University of Buenos Aires
Spanish, English
Github Skills (10)
pandas10
exploratory-data-analysis10
python10
data-science10
eda10
data-analysis10
machine-learning9
data-visualisation9
data-visualization9
data-visualizations9
Programming languages (3)
Github contributions (5)
institutohumai/cursos-python
Jun 2020 - Nov 2021
Cursos completos de IA dictados por Humai
Role in this project:
Data Scientist
Data ScientistContributions:37 reviews, 78 commits, 114 PRs in 1 year 5 months
Contributions summary:Maria's primary contribution involves working on a practical exercise related to the analysis of agricultural estimations. They focused on exploratory data analysis, using Pandas to explore and transform the dataset. The user's work included data cleaning, feature engineering (extracting year and month from a combined date column), and data visualization techniques. They provided an example of the data and how it should be processed.
cursospythonpordata-sciencedeep-learning
githubmg/buildon-workshop
Oct 2019 - Apr 2021
Contributions:15 pushes, 1 branch in 1 year 6 months
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