Resume Advisor

AI-Powered Resume Analysis, Candidate Intelligence & Career Recommendation Platform

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Project Vision

Resume Advisor was built to solve one of the most common challenges faced by students and professionals:

"How do I know whether my resume is actually good enough for the role I want?"

Traditional resume reviews are subjective, inconsistent, and often expensive. Resume Advisor introduces a data-driven approach by combining Natural Language Processing, resume parsing, analytics, and recommendation systems into a unified platform that can automatically:

✅ Extract candidate information

✅ Analyze profile strength

✅ Detect missing skills

✅ Generate personalized recommendations

✅ Suggest learning pathways

✅ Provide actionable resume improvement insights

The result is a scalable resume intelligence platform capable of transforming static resumes into structured career insights.

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System Architecture

                          PDF Resume
                               │
                               ▼
                   Resume Upload Interface
                               │
                               ▼
                    Resume Processing Layer
                               │
                               ▼
                     NLP Parsing Engine
                               │
       ┌───────────────────────┼───────────────────────┐
       ▼                       ▼                       ▼
   Skills Parser         Education Parser      Experience Parser
       │                       │                       │
       └───────────────────────┼───────────────────────┘
                               ▼
                    Candidate Profiling Layer
                               │
                               ▼
                     Resume Scoring Engine
                               │
                               ▼
                      Skill Gap Detection
                               │
                               ▼
                 Recommendation Generation
                               │
                               ▼
                   Analytics & Visualization
                               │
                               ▼
                         MySQL Database

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🛠 Technology Stack

Core Technologies

Data Processing & Analytics

Pandas • NumPy • Plotly

NLP & Resume Intelligence

spaCy • pyresparser • pdfminer3

Frontend & User Experience

Streamlit Dashboard • Interactive Visualizations

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Key Features

Intelligent Resume Parsing

The platform automatically extracts and structures candidate information from uploaded PDF resumes.

Extracted Information

• Full Name
• Contact Information
• Email Address
• Phone Number
• Educational Qualifications
• Work Experience
• Technical Skills
• Certifications
• Projects
• Resume Metadata

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Candidate Profiling Engine

Transforms unstructured resume data into a structured candidate profile.

Profile Dimensions

• Education Strength
• Experience Maturity
• Skill Coverage
• Technical Competency
• Career Readiness
• Professional Development Indicators

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Resume Quality Assessment

Evaluates resumes using multiple scoring dimensions.

Assessment Parameters

Parameter	Description
Skills Coverage	Measures technical competency breadth
Resume Completeness	Detects missing sections
Education Profile	Evaluates academic background
Experience Strength	Assesses professional experience
Presentation Quality	Reviews structure and readability
Content Quality	Measures resume effectiveness

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Skill Gap Analysis

Identifies missing competencies and opportunities for professional growth.

Example Insights

• Missing Machine Learning fundamentals
• Limited cloud computing exposure
• Absence of relevant certifications
• Lack of project diversity
• Weak technical keyword coverage

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Recommendation Engine

Generates role-specific recommendations based on detected skills and career objectives.

Supported Domains

• Artificial Intelligence
• Machine Learning
• Data Science
• Software Engineering
• Full Stack Development
• Cloud Computing
• Cybersecurity
• Business Analytics

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Analytics Dashboard

Interactive dashboards built using Plotly provide detailed candidate insights.

Dashboard Components

• Resume Score Distribution
• Skills Analytics
• Candidate Statistics
• Recommendation Trends
• Feedback Metrics
• Platform Usage Statistics

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Database Layer

MySQL powers all persistent storage requirements.

Stored Entities

• Candidate Profiles
• Resume Metadata
• Recommendations
• Feedback Records
• User Activity
• Administrative Reports

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Repository Structure

Resume-Advisor/
│
├── main.py
│
├── resume_advisor/
│   │
│   ├── parser/
│   ├── recommendation/
│   ├── scoring/
│   ├── analytics/
│   ├── dashboard/
│   ├── feedback/
│   ├── database/
│   └── utilities/
│
├── uploads/
│
├── requirements.txt
│
└── README.md

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Installation

git clone <repository-url>

cd Resume-Advisor

python -m venv venv

venv\Scripts\activate

pip install -r requirements.txt

python -m spacy download en_core_web_sm

streamlit run main.py

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Admin Access

Username : admin
Password : admin@omjee

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Engineering Highlights

Software Engineering

• Modular Architecture
• Separation of Concerns
• Reusable Components
• Database Abstraction Layer

Data Engineering

• Automated Resume Processing
• Structured Data Extraction
• Persistent Data Storage

Machine Learning & NLP

• Named Entity Recognition
• Resume Parsing
• Skill Extraction
• Candidate Profiling

Product Design

• Interactive Dashboard
• User Feedback System
• Admin Analytics Panel
• Recommendation Framework

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Future Roadmap

Phase 1

• ATS Compatibility Scoring
• Job Description Matching
• Resume Benchmarking

Phase 2

• LLM Resume Reviewer
• AI Resume Rewriting
• Cover Letter Generation

Phase 3

• Recruiter Dashboard
• Resume Ranking System
• Candidate Shortlisting Engine

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Author

Omjee R. Giri

AI & Machine Learning Engineer • Data Science Enthusiast • Competitive Programmer

"Building intelligent systems that transform unstructured information into actionable insights."