Gabriel Spinardi
Computer Scientist, Business Management Specialist, Postgraduate in Data Science and Analytics and Entrepreneur
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Entrepreneur and Computer Scientist graduated in 2021 at FEI - Fundação Educacional Inaciana.
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Experience with IT Governance at Itaú and with Online Sales Management at GPS Eletrônicos website.
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Certifications in Machine Learning, Python, Data Science and Artificial Intelligence.
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Studying a Master of Business Administration in Business Management at USP/Esalq.
PROFESSIONAL
MY KNOWLEDGE IN TOOLS
SQL
100%
EXCEL
100%
JAVA
100%
HTML/CSS
100%
++C/C
100%
PYTHON
100%
JAVASCRIPT
100%
MAXIMUM/JIRA
100%
NET.
100%
#W
100%
R
100%
Academic PORTFOLIO
Experiences
2024
MBA in Data Science and Analytics at USP
Specialization Course
MBA in Data Science and Analytics at USP/Esalq.
2022
Gabriel Spinardi IT Solutions
CEO
IT services support and assistance company.
2022
MBA in Business Management at USP
Specialization Course
MBA in Business Management at USP/Esalq.
2021
GPS Electronics
2019
Network (Itaú)
CEO
Online retail company, in the dropshipping business of electronic products.
Functional Tests
Performance in functional tests on the Network's "contactless" machines, focusing on testing operators, types of transactions and different banking domiciles.
2018
Network (Itaú)
2017
Network (Itaú)
Problem Management
Analysis of problem records, forwarded to the responsible troubleshooting area and participation in committees to resolve failures, proposed by ITIL.
Change Management
Management of all reports (infrastructure changes, systemic changes, emergency systemic changes and cloud changes) for analysis and validation, always in accordance with ITIL processes. Also carried out negotiations for cloud changes and generation of documentation for internal and external audits.
2016
Scientific Initiation
Cognitive Computer Vision
In this project, OpenCV was used to define AI-based features using an RGB scale and an algorithm was defined that aimed to separate lines from scenes captured by webcam so that it could be implemented in a robot in the future. The final objective was to optimize a code to highlight and define the edges of environments, thus allowing the robot to move autonomously, avoiding objects such as walls, tables, chairs, etc.
CERTIFICATIONS
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