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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.