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juanludataanalyst/README.md

Data-Driven Value Creator 💎

Leveraging data into business opportunities 💰


🚀 Main Projects

Your personal AI assistant for job applications. Effortlessly transform your PDF resume to perfectly match any job description and maximize your chances of passing Applicant Tracking Systems (ATS).

🔗 Live App: CV Adapter – ATS Optimizer
🔗 GitHub Repository: CV Adapter – ATS Optimizer

CV Adapter Video Demo

Key Features:

  • AI-powered Adaptation: Uses LLMs to rewrite your CV, highlighting relevant skills and keywords based in the job
  • ATS Score Calculation: See your match score before and after optimization.
  • Download & Export: Get your new CV as PDF or YAML for editing
  • Modern, User-Friendly UI: Built with Streamlit for a seamless experience.

How It Works

  1. Upload your CV as a PDF using a simple drag-and-drop interface.
  2. Paste a job description (either as a URL or full text). If you provide a URL, the app will automatically scrape and extract the job details for you.
  3. AI analyzes your CV and the job description: The system compares your experience, skills, and keywords with those required in the job offer using advanced language models.
  4. Your CV is adapted and optimized: The app rewrites and restructures your resume to highlight the most relevant information for the job, maximizing your ATS score and visibility to recruiters.
  5. Get instant feedback: See your ATS match score before and after optimization, so you know exactly how your CV has improved.
  6. Download your optimized CV as a PDF, HTML, or YAML file, or upload it directly to your Google Drive for easy sharing and safekeeping.
  7. Apply with confidence: Use your tailored CV to stand out in any application process, whether in English or Spanish.

Example Use Cases

  • Applying to jobs in different countries or sectors
  • Quickly adapting your CV for multiple applications
  • Improving interview chances by targeting keywords

A smart job portal for the tech sector that uses AI and semantic search to recommend the most relevant job offers to each user.

🔗 Live App: Tech Job Portal
🔗 GitHub Repository: Tech Job Portal

Tech Job Portal Demo

Key Features:

  • Semantic Search: Find tech jobs using natural language and AI-powered matching.
  • AI Explanations: Get clear, automatic explanations of why each job fits your profile.
  • Modern, Intuitive UI: Built with Streamlit and custom CSS for a smooth user experience.
  • Easy to Use: Just run and explore – no technical setup required!

How It Works

1️⃣ Data Collector: The portal loads and organizes job offer data from multiple sources, storing them in structured files for efficient access.

2️⃣ Embeddings Generation: Each job offer is converted into a high-dimensional vector using state-of-the-art language models (sentence-transformers). This allows the system to understand the meaning and context of each job description.

3️⃣ Semantic Matching: When a user enters a search query, it is also embedded into a vector. The system calculates the similarity between the user query and all job offers using cosine similarity, surfacing the most relevant results.

4️⃣ AI-Powered Explanations: For each search, the portal uses large language models (via Together AI) to generate clear, personalized explanations of why each job offer matches the user’s query.

5️⃣ Interactive Experience: All results and explanations are presented in a modern, interactive Streamlit interface, making it easy to explore opportunities and understand your best matches.

This project empowers tech professionals to discover new job opportunities and understand the reasoning behind each recommendation.


This web application helps professionals identify the most sought-after skills for different job roles across various countries. It also provides personalized recommendations on which skills to learn next based on user input, leveraging machine learning techniques and web scraping from multiple job portals.

🔗 Live App: Most In-Demand Skills App

🔗 GitHub Repository: Most In-Demand Skills

Most In-Demand Skills App Screenshot

Key Features:

  • Job Market Analysis: The app gathers and processes job postings from various sources to extract the most frequently mentioned skills for different roles and regions.
  • Smart Analysis & Personalized Recommendations: Using machine learning algorithms, the app detects patterns and relationships between skills. Based on the user’s existing skill set, it suggests additional skills to enhance job market competitiveness.
  • User-Friendly Interface: Built with Streamlit, ensuring an intuitive and interactive experience.

How It Works

1️⃣ Data Collection: The app extracts job data from multiple job portals using web scraping and organizes it by date, country, and role.
View code and explanation in my GitHub

2️⃣ Skill Extraction: Relevant skills are identified from job descriptions and stored in a structured format.

3️⃣ Machine Learning Integration: Association rule mining techniques uncover relationships between skills.

4️⃣ Recommendations: Users enter their current skills, and the app suggests additional skills to learn, optimizing employability prospects.

This tool is designed to assist job seekers and professionals in making data-driven decisions about skill development, ultimately improving their career opportunities.


A fully automated data pipeline for collecting and processing reservation data for Hostal R10, built with Python.

🔗 GitHub Repository: Data Pipeline Hostal R10


🎤 Talks

📹 Tidyverse for Data Analysis - Sevilla R Users Group
A talk about using the tidyverse library in R for data analysis, presented at the Sevilla R Users Group.

YouTube Video Thumbnail


🛠 Tech Stack

Python      R      SQL      Power BI


📫 Connect with me

LinkedIn
GitHub


Made with ❤️ by Juan Luis Pérez

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