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AI-Based Resume Screening Tool

A Python-based AI/ML platform that automates resume screening by analyzing and ranking candidates based on their fit with job descriptions using natural language processing techniques.

PythonNLP (NLTK, SpaCy)DjangoPostgreSQLPandasNumPyscikit-learnREST APIs
8 technologies
Updated 07/2023
Full-stack Application

AI-Based Resume Screening Tool

Next cohort starts: 21-11-2025

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Project Architecture

Comprehensive overview of the project architecture, features, and development process with modern design patterns

Project Features

Discover the comprehensive feature set that powers this application

Core Features

Automated resume parsing and keyword extraction
Candidate ranking based on job description matching
Role-based access for HR Admin and Recruiters
Dashboard to view candidate scores and summaries
Exportable candidate reports (CSV/PDF)
Secure login and data access control

Operational Features

Integration with email for job application submissions
Customizable scoring and ranking criteria
Batch processing of multiple resumes
Notifications for shortlisted candidates
Search and filter resumes by skills, experience, or education

Analytics & Reporting

Candidate selection trends and statistics
Job role success rate and application insights
Resume keyword analysis and frequency reports
ML model performance metrics for accuracy and precision

System Architecture

Explore the technical foundation and architectural decisions

Frontend Architecture

Framework

Django Templates (HTML/CSS/JS)

State Management

Django Context & Client-side JS

Charts Library

Chart.js / Plotly for candidate analytics

AI Integration

NLTK, SpaCy, scikit-learn for ranking and matching

UI Libraries

BootstrapDataTables

Backend Architecture

Framework

Django

Database

PostgreSQL

Authentication

Django Authentication with JWT

Real-time Communication

AJAX polling / Django Channels for updates

AI Services

Resume Parsing & Scoring

NLP (NLTK, SpaCy) and ML Models

Job Description Matching

TF-IDF Vectorization and Similarity Scoring

Development Phases

Strategic roadmap for project implementation and delivery

1

Project Setup & Authentication

1-2 weeks
Initialize Django project structure
Configure PostgreSQL database
Implement user authentication and role-based access
Set up models for resumes, candidates, and job descriptions
2

Resume Parsing & ML Integration

2-3 weeks
Develop resume parsing module using NLP
Implement candidate scoring and ranking algorithms
Integrate job description matching logic
Store and retrieve candidate scores from database
3

Dashboard & Reporting

2 weeks
Create recruiter dashboard with rankings and filters
Visualize candidate analytics using charts
Add export functionality (CSV/PDF)
Implement notifications for shortlisted candidates
4

Testing & Optimization

1 week
Unit and integration testing for backend and ML models
Validate ranking and matching accuracy
Optimize database queries and dashboard performance
Conduct end-to-end testing for recruiter workflow

API Endpoints

RESTful API structure and endpoint organization

Authentication

Register User

POST /api/auth/register

Login

POST /api/auth/login

Get User Profile

GET /api/auth/me

Resumes

Upload Resume

POST /api/resumes/upload

Get All Resumes

GET /api/resumes

Get Resume By ID

GET /api/resumes/:id

Delete Resume

DELETE /api/resumes/:id

Candidates

Get Candidate Rankings

GET /api/candidates/rankings

Get Candidate By ID

GET /api/candidates/:id

Shortlist Candidate

POST /api/candidates/shortlist

Notifications

Send Email Notification

POST /api/notifications/email

Testing Strategy

Comprehensive quality assurance and testing methodologies

Unit Testing

pytest
unittest

Integration Testing

Django Test Framework

End-to-End Testing

Selenium
Cypress

AI Testing

Accuracy of candidate ranking and matching
NLP model validation and keyword extraction performance

Deployment Strategy

Production deployment and infrastructure management

Frontend

Heroku / Vercel

Backend

AWS EC2 / Heroku

Database

PostgreSQL

CI/CD

GitHub Actions

Future Enhancements

Roadmap for upcoming features and improvements

Resume keyword heatmap visualization
Integration with LinkedIn API for direct candidate import
AI-driven interview question suggestions
Multi-language support for global candidates
Automated feedback generation for applicants