Miguel de Sousa

Data Scientist

https://talent.gravityer.com/miguel-de-sousa

Electrical Engineering Msc Student @ COPPE - Universidade Federal do Rio de Janeiro.

Rio de Janeiro, Rio de Janeiro, Brazil

Key Strengths

Demonstrated interest in Data Science and Machine Learning through projects like 'CPE727-2025-03' (Deep Learning) and 'worlds_simplest_instrument_classifier'.
Proficiency in Python, a core language for Data Science, evidenced by multiple projects.
Experience with Jupyter Notebook, a standard tool for data exploration and model development.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects show a strong academic and personal interest in various technical domains, including deep learning, audio processing, and mobile development. This indicates a curious and self-motivated individual. However, the projects are predominantly personal/academic and lack explicit team collaboration or real-world business impact, making it difficult to fully assess cultural fit for a professional team environment. The diversity of technologies (Python, Swift, C++, Java, JavaScript) suggests adaptability, but also a potential lack of deep specialization in a single area relevant to the target role.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

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Projects

ios-tse-models

June 15, 2026 – Present

ios-tse-models — GitHub repository

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ainda

March 6, 2026 – Present

ainda — GitHub repository

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CPE727-2025-03

September 25, 2025 – December 18, 2025

Repositório para ser utilizado durante a disciplina do PEE (Programa de Engenharia Elétrica) da Coppe/UFRJ CPE727 Aprendizado Profundo, período 2025/03. Professor Responsável: Natanael Nunes de Moura Junior

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recital_ios_app

July 22, 2025 – July 22, 2025

recital_ios_app — GitHub repository

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pkmn_tcgp_bulba

November 5, 2024 – November 5, 2024

Python scrapper for getting Pokémon Trading Card Game Pocket (TCGP) mobile game.

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CPE793-topics-in-audio-codification

August 12, 2021 – November 19, 2021

CPE793-topics-in-audio-codification — GitHub repository

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audioroute_poc

July 29, 2021 – August 2, 2021

audioroute_poc — GitHub repository

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worlds_simplest_instrument_classifier

July 5, 2020 – October 5, 2021

The world's simplest instrument classifier, using Constant-Q Transform and Logistic Regression.

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Trabalho-de-CE2

June 23, 2016 – July 24, 2016

Trabalho-de-CE2 — GitHub repository

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Profedex

June 8, 2016 – August 2, 2016

Profedéx is an Android Application developed by UFRJ students for UFRJ students.

View Project

Key Strengths

Demonstrated interest in Data Science and Machine Learning through projects like 'CPE727-2025-03' (Deep Learning) and 'worlds_simplest_instrument_classifier'.
Proficiency in Python, a core language for Data Science, evidenced by multiple projects.
Experience with Jupyter Notebook, a standard tool for data exploration and model development.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

Miguel de Sousa

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit