David Camilo Muñoz

Data Scientist

https://talent.gravityer.com/david-camilo-munoz

Trying to be Consistent

Popayán, Cauca Department, Colombia

Key Strengths

Demonstrated proficiency in various machine learning techniques including Reinforcement Learning, NLP, Computer Vision, and classic ML algorithms (XGBoost, Random Forests).
Extensive practical experience with Python and Jupyter Notebook for data science projects.
Experience with deep learning frameworks such as TensorFlow/Keras and PyTorch.
Strong project-based learning approach, tackling diverse problems from network routing to image enhancement and hate speech detection.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio demonstrates a strong interest in diverse applications of data science and machine learning, indicating adaptability and a proactive learning attitude. However, the projects are all personal, which might suggest a preference for independent work. Without team-based project experience or explicit collaboration details, assessing cultural fit for a collaborative team environment is challenging.

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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Assessing your cultural and operational fit

Projects

world_cup_2026

May 2, 2026 – Present

world_cup_2026 — GitHub repository

View Project

text_classification_comparison

July 14, 2025 – July 14, 2025

A comparison of a classic neural network and a Transformer-based model for text classification on the 20 Newsgroups dataset using TensorFlow/Keras.

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hate_speech_analysis

July 14, 2025 – July 14, 2025

Hate speech detection using NLP for linguistic analysis and machine learning (XGBoost) for classification with Python and SpaCy.

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deforest_amazonia

June 17, 2025 – July 14, 2025

Analysis of deforestation in the Jamanxim National Forest (2000-2019) through a computer vision pipeline that segments and quantifies affected areas from satellite imagery.

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low_light_enhancer

May 8, 2025 – July 14, 2025

A comparison of classical image processing vs. the Zero-DCE++ deep learning model for unsupervised low-light image enhancement using PyTorch

View Project

portfolio

October 8, 2022 – Present

My Portfolio Website

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P4Tree

October 2, 2022 – October 2, 2022

A novel approach based on Random Forests that quickly and accurately identifies elephant flows in programmable Data Planes.

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qatar_2022_prediction

September 26, 2022 – November 13, 2023

QATAR 2022 World Cup prediction from the international matches played since the 90s, the qualifications of the teams in their last matches, and the potential of each team.

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routing_reinforcement_learning

February 19, 2022 – March 15, 2022

Reinforcement Learning (RL)-based routing algorithm for SDN networks created from scratch using Python.

View Project

speedylinefollowing_robot

February 13, 2022 – March 15, 2022

Speedy Line Following Robot with Arduino

View Project

Key Strengths

Demonstrated proficiency in various machine learning techniques including Reinforcement Learning, NLP, Computer Vision, and classic ML algorithms (XGBoost, Random Forests).
Extensive practical experience with Python and Jupyter Notebook for data science projects.
Experience with deep learning frameworks such as TensorFlow/Keras and PyTorch.
Strong project-based learning approach, tackling diverse problems from network routing to image enhancement and hate speech detection.

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.

David Camilo Muñoz

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit