ScreenSmart - AI-Powered Resume Screener

By Team SOS

At Coherence-25 hackathon

Team Members:

• Liza Castelino
• Romeiro Fernandes
• Gavin Soares
• Russel Daniel Paul

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🚀 Problem Statement

In today’s competitive job market, HR teams struggle to efficiently screen thousands of resumes.
The hiring process is:

• Time-consuming – Manual screening takes hours per candidate.
• Inconsistent – Prone to human errors and bias.
• Inefficient – Matching candidates with job descriptions is difficult.

🔹 Goal

Develop an AI-powered resume screening system that automates candidate ranking based on:

• Job Descriptions
• Skills & Experience
• Bias-Free Selection

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🛠️ Solution Approach

1️⃣ Resume Processing & Data Extraction

• NLP (Natural Language Processing) extracts key information from resumes.
• Scrapy is used for structured data extraction.
• Gemini AI ensures typo-free and clean resume data.

2️⃣ AI-Based Candidate Matching

• XGBoost ML Model assigns a hirability score based on past hiring data.
• SWOT Analysis evaluates strengths, weaknesses, opportunities, and threats.

3️⃣ Web Dashboard for HRs

• Upload resumes and job descriptions.
• View ranked candidates with AI-driven insights.
• Compare candidates side-by-side.
• Automated email notifications for shortlisted applicants.

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