Resume Matcher

What is the project about?

Resume Matcher is an AI-powered, free, and open-source tool designed to help job seekers tailor their resumes to specific job descriptions. It analyzes both the resume and the job description to identify matching keywords, assess readability, and provide insights for improvement.

What problem does it solve?

The project addresses the challenge of Applicant Tracking Systems (ATS) filtering out resumes that don't contain the right keywords or are poorly formatted. Many qualified candidates are rejected before a human ever sees their resume. Resume Matcher helps applicants optimize their resumes to pass ATS scans and increase their chances of getting an interview. It helps applicants to tailor their resume to the job description.

What are the features of the project?

Resume and Job Description Parsing: Uses Python to parse the text content of resumes and job descriptions, mimicking ATS functionality.
Keyword Extraction: Employs machine learning algorithms to identify the most important keywords from the job description.
Key Terms Extraction: Identifies the main themes and concepts within the job description using textacy.
Vector Similarity Matching: Calculates the similarity between the resume and job description using FastEmbed, a highly efficient embedding system. This provides a score indicating how well the resume matches the job requirements.
Readability Improvement Suggestions: (Implied, but not explicitly detailed in the features list) Offers insights to enhance the resume's readability.
ATS Optimization Guidance: Provides suggestions to make the resume more ATS-friendly.
Streamlit Web App: A user-friendly interface for interacting with the tool.
Docker Support: Allows for easy deployment and execution in a containerized environment.
Google Colab Support: The project can be run in Google Colab.
Full Stack Web Application: (Under Development) A Next.js (React and FastAPI) web application is being developed, though currently returns mocked results.
Pre-commit Hooks: Uses pre-commit to automatically check for common issues before commits are submitted.

What are the technologies used in the project?

Python: The core language for parsing, analysis, and backend logic.
Machine Learning Algorithms: (Not specified, but likely NLP techniques) Used for keyword extraction.
FastEmbed: A library for fast and efficient text embedding and similarity calculation.
textacy: A Python library built on spaCy for higher-level natural language processing tasks.
Streamlit: A framework for creating interactive web applications for data science and machine learning.
Docker: A platform for containerizing and deploying applications.
Next.js (React & FastAPI): (For the full-stack web app, currently under development) A React framework for the frontend and a FastAPI framework for the backend API.
Tailwind CSS: A utility-first CSS framework.
TypeScript: A superset of JavaScript that adds static typing.
HTML/CSS: For web page structure and styling.
Black: A code formatter for Python.
Pre-commit: A framework for managing and maintaining pre-commit hooks.
Ngrok: Used in the Google Colab version.

What are the benefits of the project?

Increased Interview Chances: Helps applicants create ATS-friendly resumes, improving their chances of getting past initial screening.
Targeted Resumes: Enables users to tailor their resumes to specific job requirements by highlighting relevant skills and experience.
Time Savings: Automates the process of identifying keywords and optimizing resume content.
Free and Open Source: Accessible to everyone, with the opportunity for community contributions and improvements.
Easy to Use: The Streamlit interface provides a simple and intuitive way to use the tool.
Easy to Deploy: Docker support simplifies deployment.

What are the use cases of the project?

Job Seekers: Individuals applying for jobs can use the tool to optimize their resumes for specific positions.
Career Counselors: Career advisors can use the tool to help clients improve their resumes.
Students: Students entering the job market can use the tool to create effective resumes.
Anyone updating their resume: The tool can be used whenever someone wants to update their resume and tailor it to a specific job or industry.