Hire3x Smart Rank is an intelligent hiring support system that automatically evaluates and ranks
candidates for multiple job roles based on skills similarity, experience level,
and text-based matching algorithms.
The platform uses advanced NLP scoring (Cosine Similarity), rule-based skill filtering, and a data-driven ranking
engine to help recruiters quickly identify top candidates. It is built using Streamlit, ensuring
a smooth, interactive, and real-time experience.
This solution is ideal for HR teams, startups, placement cells, and automated hiring workflows
that want to eliminate manual resume screening and move to instant, data-backed hiring decisions.
⚙️ Core Concept
The main idea behind Hire3x Smart Rank is:
“To make hiring faster, smarter, and unbiased through automated skill–experience matching.”
The system achieves this by:
AI-driven similarity comparison between job skills and candidate skills
Weighted scoring based on experience match
Filtering options for strict or flexible skill requirements
Visual charts to understand candidate ranking at a glance
Exportable CSV reports for recruiters and HR teams
The goal is to reduce manual effort and bring consistency, transparency, and intelligence into the hiring process.
🧠 Working Process
1️⃣ Upload Job Requirements
Recruiters upload a Job CSV with the following columns:
Job Title
Required Skills
Minimum Experience
Example row: Software Engineer | Python, Flask, SQL | 2
2️⃣ Upload Candidate Profiles
Recruiters upload a Candidate CSV with the following columns:
Name
Skills
Experience (numeric value in years)
Example row: Aarav Kumar | Python, SQL, Data Analysis | 2
3️⃣ Skill Filtering
Before ranking, the system applies a skill filter based on recruiter choice:
ANY Required Skill → Candidate must match at least one required skill
ALL Required Skills → Candidate must match every skill listed in the job
This helps recruiters switch between strict and flexible matching modes.
4️⃣ Smart Match Calculation
For each candidate that passes the skill filter:
Skills text is compared with job skills using Cosine Similarity (CountVectorizer-based).
Experience is normalized against the job’s minimum experience.
Final score formula: Final Match % = 70% Skills Score + 30% Experience Score
The result is a clear Match % for every candidate.
5️⃣ Ranking & Visual Analysis
Candidates are sorted in descending order of Match %.
Matched skills are highlighted in bold for better readability.
An interactive bar chart (Plotly) shows compare-at-a-glance ranking per job.
Recruiters can download the ranked list as a CSV report.
6️⃣ Recruiter Decision
The interface clearly displays:
🎯 Top matching candidate per job
📊 Full ranked candidate list with skills and experience
⬇️ Download button for exporting results
This enables fast, confident decision-making for each role.
🔍 Technologies Used
UI / Framework
Streamlit for building an interactive, web-based data app.
Backend Logic
Python functions implementing ranking, filtering, and score calculation.
Data Handling
Pandas for reading CSV files, cleaning data, and generating ranked outputs.
NLP Skill Matching
scikit-learn’s CountVectorizer and cosine_similarity to compare skills text.
Visualization
Plotly Express bar charts for visualizing candidate Match % per job.
Export & Reports
CSV export of ranked candidates per job for HR team usage.
Deployment (Optional)
Streamlit Cloud / HuggingFace Spaces for online hosting and demo access.
Version Control
Git & GitHub to manage source code and project versions.
🎯 Main Features
📁 Upload Job CSV and Candidate CSV directly in the app
🔍 AI-powered skill matching using cosine similarity
📈 Weighted scoring combining both skills and experience
🎯 Automatic identification of the Top Candidate per job
⚡ Match candidates for multiple job roles in one go
🔎 Skill filter modes — ANY or ALL required skills
🖊️ Highlighted skill matches in candidate profiles for clarity
📊 Interactive bar charts to visualize match percentages
⬇️ One-click CSV export of ranked results
🧭 Simple, fast, and recruiter-friendly interface
🌈 Example Output
For Job: Python Developer
Required Skills: Python, Flask, SQL
Minimum Experience: 2 years
System Output (sample ranking):
Name
Skills
Experience (years)
Match %
Aarav Kumar
Python, SQL, Data Analysis
2
92.4
Vikram Singh
Python, Machine Learning
2
85.1
Ananya Iyer
HTML, CSS, JavaScript
1
22.8
The app highlights: Top Candidate: Aarav Kumar 🎯 and displays a Plotly bar chart to visually compare
match percentages across all candidates.
🧩 Future Scope
🤖 AI resume parsing to extract skills and experience directly from PDF resumes
🔎 JD analyzer to auto-extract skills from unstructured job descriptions
📂 Integration into a full Applicant Tracking System (ATS)
🧠 Deep learning–based similarity models for richer matching
🌍 Batch processing for large-scale, multi-job hiring pipelines
🧾 Candidate scoring explanation — “Why this %?” for transparency
📱 Mobile-friendly UI or dedicated mobile app
🔐 Role-based login and dashboards for HR teams and managers
📊 HR analytics dashboard for insights on talent pool and hiring trends
💡 Vision Statement
“To transform hiring into a fast, fair, and intelligent process by using AI-driven matching and data-backed decision-making.”