RecruitIQ- HR Recruiting Suite

RecruitIQ, as a project, addresses the critical needs of modern HR departments by automating recruitment workflows, enhancing candidate engagement, and providing actionable insights through analytics. Its modular design and robust tech stack allow for easy customization and integration, making it a valuable asset for efficient and data-driven talent acquisition

Project Features

1. Resume Analyzer

• Automated Data Extraction: AI algorithms scan resumes in various formats (PDF, DOCX, TXT, etc.) and extract structured data such as personal details, work experience, education, skills, certifications, and languages.

• Natural Language Processing (NLP): Utilizes NLP to accurately interpret and categorize information, even in complex or multilingual resumes.

• Keyword and Skill Matching: Identifies and highlights relevant skills, experience, and job-specific keywords, enabling more effective candidate-job matching.

• Bias Reduction: Configurable parsing fields help minimize unconscious bias in candidate screening.

• Bulk Processing: Parses large volumes of resumes quickly, saving significant recruiter time and effort.

• Integration: Seamlessly connects with Applicant Tracking Systems (ATS) and other HR platforms for efficient workflow management

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2. AI-Driven Employee Sentiment Analysis

• RecruitIQ and similar platforms employ AI to analyze employee sentiment, providing deep insights into workforce morale and engagement:

• Sentiment Detection: Uses NLP and machine learning to analyze employee communications (emails, chat messages, survey responses) and determine sentiment—positive, neutral, or negative.

• Real-Time Feedback: Delivers instant insights on employee satisfaction, allowing organizations to address issues proactively.

• Pain Point Identification: Detects common concerns and dissatisfaction trends, enabling targeted interventions.

• Personalized Experience: AI tailors recommendations for benefits, training, and communication based on individual sentiment analysis.

• Predictive Analytics: Identifies employees at risk of disengagement or turnover, supporting timely retention actions.

Installation ⬇️

Clone the repository:

git clone https://github.com/yourusername/HR_Recruiting-Suite.git
cd RecruitIQ-pro

Create a virtual environment to isolate the project dependencies:

python -m venv myenv

Activate the virtual environment:

🪟 On Windows:

myenv\Scripts\activate

💻 On macOS/Linux:

source myenv/bin/activate

• ⬇️ Install dependencies: Ensure you have Python installed, then install the required libraries:

pip install -r requirements.txt 

Run the application:

streamlit run app2.py

Demo

See demo below: [![RecruitIQ] // Title (https://github.com/SankethSingh/HR_Recruiting-Suite/blob/master/static/Dash_Resume.png)] // Thumbnail (https://github.com/SankethSingh/HR_Recruiting-Suite/blob/master/static/demo_1.mp4) // Video Link https://github.com/SankethSingh/HR_Recruiting-Suite/blob/master/static/demo_1.mp4

Screenshots

• Dashboard Resume Page

• Dashboard Sentiment Analysis

Contributing

Contributions are always welcome!

Please adhere to this project's code of conduct.