Carlos Mejia

Data Scientist

https://talent.gravityer.com/carlos-mejia

Cloud DevOps Engineer / Data Engineer

Munich, Bavaria, Germany

Key Strengths

Demonstrated interest in Data Science and MLOps through personal projects.
Proficiency in Python, Jupyter Notebook, and related data science tools.
Experience with CI/CD concepts and containerization (Dockerfile) in personal projects.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's personal projects show a strong inclination towards learning and applying new technologies, particularly in the data science and MLOps domains. The diversity of projects, including those related to AWS ML Foundations and Hands-On Machine Learning, indicates a proactive and self-driven learning approach. However, the lack of professional experience or team-based projects makes it difficult to fully assess collaboration and broader cultural fit.

Soft Skills & Operational Fit

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

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Assessing your cultural and operational fit

Projects

itesm-cicd-demo

August 14, 2025 – August 15, 2025

Demo for CI/CD

View Project

team-LECture-bot

May 1, 2025 – July 20, 2025

team-LECture-bot — GitHub repository

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tum-idp

December 6, 2024 – April 22, 2025

TUM Interdisciplinary Project

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calculator

December 6, 2024 – April 7, 2025

Simple calculator

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itesm-mlops-project

August 21, 2023 – August 24, 2023

ITESM MLOPs Project

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itesm-mlops

July 10, 2023 – August 22, 2023

Acerca del curso

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ide-luis-ferrer

June 17, 2023 – September 7, 2023

This repo contains the content and code of Introduction to Data Engineering

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aws_machine_learning_foundations_udacity

August 1, 2021 – October 12, 2021

This repository has the notes, codes and more of the course AWS Machine Learning Foundations Course by Udacity

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carloslme

July 29, 2021 – Present

My personal repository

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handson-ml2-book

February 27, 2021 – June 13, 2021

Summary and customized notes and scripts from Hands-On Machine Learning Book

View Project

Key Strengths

Demonstrated interest in Data Science and MLOps through personal projects.
Proficiency in Python, Jupyter Notebook, and related data science tools.
Experience with CI/CD concepts and containerization (Dockerfile) in personal projects.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

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

Carlos Mejia

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit