| Machine Learning Engineer at Agi | MSc. Computer Science
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Agibank
Data Scientist
June 23, 2026 – Present
strava-to-trainingpeaks
April 10, 2024 – Present
This is a simple script that will download your activities from Strava and upload them to TrainingPeaks in assisted mode.
View Projecteucalyptus-count
September 19, 2023 – September 25, 2023
🌲🧮 Eucalyptus counting using artisanal methods and computer vision.
View ProjectUSeS-BPCA
July 11, 2023 – January 3, 2024
🧠💻 USeS-BPCA: U-Net Semantic Segmentation BPCA Pooling
View Projectmasters-degree-in-computer-science-from-unesp
April 30, 2023 – May 2, 2024
Master's Degree in Computer Science from UNESP
View Projectstudy_segmentation
May 19, 2022 – January 3, 2023
This repository was created to store learning of the Image Segmentation from A to Z course.
View Projectstrava-analysis
November 4, 2021 – March 28, 2025
🏃📊 Using strava to do personal analyses and to practice data scientist skills.
View ProjectNkocr
July 7, 2020 – Present
🔎📝 This is a module to make specifics OCRs at food products and nutritional tables.
View ProjectCoffee_Recognize_API
July 22, 2019 – February 14, 2024
This is my graduation project api, made with nodeJS and Tensorflow. The objective is to process images to classify and find area of leaf disease in coffee culture.
View ProjectCoffee_Recognize
June 25, 2019 – Present
🌱🔎 This is my graduation project. The objective is to detect the disease in the coffee leaf and the contamination percentage.
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and academic, demonstrating strong individual initiative and a passion for learning. However, there is limited evidence of team-based projects or contributions to open-source communities, which could indicate a need for further assessment of collaborative cultural fit. The projects align well with a data scientist role, showing a clear interest in the domain.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are concise, but there is no information on collaboration, problem-solving approaches, or communication style.