Joseba Fuentes
Data ScientistMinsait
Member since June 21, 2026
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Minsait
Data Scientist
June 21, 2026 – Present
killpy
January 2, 2025 – Present
🐍 CLI tool to find and delete unused Python virtual environments (.venv, poetry, conda, pipenv, uv). Reclaim disk space effortlessly — supports bulk delete, size reporting, and pycache cleanup.
View Projectfake-rtsp
July 30, 2023 – Present
Fake RTSP camera streams via Docker — simulate any camera fleet for NVR, VMS, and computer vision testing
View Projectaipose
January 22, 2023 – Present
The aipose library provides a simple API for performing human pose estimation in computer vision projects using pre-trained deep learning models built on PyTorch and TensorFlow.
View Projectlabelme2yolov7segmentation
December 6, 2022 – December 29, 2024
Conver labelme annotation format to yolov7 annotation format for segmentation.
View Projectpython-vscode-template
August 5, 2022 – December 16, 2023
Template to develop apps in python in vscode as monorepo or as a project
View ProjectCurso-Introduccion-a-GraphQL
July 18, 2021 – July 18, 2021
Curso-Introduccion-a-GraphQL — repository
View ProjectTaller-control-de-accesso-en-GraphQL
May 15, 2021 – July 17, 2021
Taller-control-de-accesso-en-GraphQL — repository
View Projectfile-explorer-utils
December 21, 2020 – December 28, 2020
file-explorer-utils — repository
View Projectjpg2xlsx
August 30, 2016 – Present
Python library for converting JPG images into Excel files by mapping each pixel to a cell background color.
View ProjectCultural Fit Analysis
The candidate's personal projects demonstrate a strong inclination towards open-source contributions and practical problem-solving, which aligns with a culture of innovation and self-driven learning. However, the projects are heavily focused on Python utilities and computer vision, with less explicit demonstration of broader data science methodologies (e.g., statistical modeling, A/B testing, advanced machine learning beyond CV). The single professional experience as a Data Scientist is current but lacks detail, making it difficult to fully assess cultural fit within a team-oriented data science environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a proactive approach to problem-solving and tool development.