This project allows users to extract data from LinkedIn profiles and job postings to:
- Calculate a matching score between their skills and job requirements.
- Estimate a salary range based on their skills and match score.
💡 Two Ways to Use This Tool:
- Automated: Provide LinkedIn credentials for direct data extraction.
- Manual: Upload exported HTML files from LinkedIn (for privacy-conscious users).
- 📌 Run in Google Colab → No installation needed!
- 🛡️ Privacy → Credentials are not stored or shared.
- 📊 Outputs → Matching Score & Salary Estimate.
- Google Colab (click
.ipynbfile for link) - No local installations required
- Open
Profile_Data.ipynbin Google Colab. - Click
Runtime → Run all. - Enter:
- LinkedIn Email:
your_email@example.com - LinkedIn Password:
your_password - LinkedIn Profile URL:
https://www.linkedin.com/in/your-profile-id/ - Job URL:
https://www.linkedin.com/jobs/view/job_number/
- LinkedIn Email:
- Outputs:
✅profile_data.txt(LinkedIn profile)
✅job_details.txt(Job posting)
- Examples inside Data folder
- Open
Profile_Data_Without_Auth.ipynbin Google Colab. - Click
Runtime → Run all. - Upload your saved LinkedIn HTML files:
- Experience
- Education
- Skills
- Enter the Job URL:
https://www.linkedin.com/jobs/view/job_number/ - Outputs:
✅profile_data.txt(LinkedIn profile)
✅job_details.txt(Job posting)
- Examples inside Data folder
- Open
Wage_and_Similarity.ipynbin Google Colab. - Click
Runtime → Run all. - Upload the extracted files:
profile_data.txtjob_details.txt- 'full_model.pkl' (from git folder)
- Outputs:
-
📌 Matching Score → % match & skill improvement suggestions.
-
Get information about skills you might want to improve to increase your odds of getting the job:
-
💰 Salary Range → Estimated based on skills & job market data.
-
- Credentials are used locally and never stored/shared.
- If concerned, use the manual upload method.
- Open your LinkedIn Skills Page: https://www.linkedin.com/in/my-profile/details/skills/
- Press
Ctrl + Shift + I(orCmd + Option + Ion Mac) → Open Developer Tools. - Right-click
<html>→Save As...→ Choose "Web Page, HTML Only". - Upload the
.htmlfile when running the script. - Do the same for you Education page and experience page. you should have 3 html files in total. *in a case you cant enter those sections enter /details/the section you want/ to the url line
This project is for educational purposes only.
It does not store user data, nor does it guarantee accuracy in salary estimation.
- ✅ Add support for more job platforms (e.g., Indeed, Glassdoor).
- ✅ Improve salary model accuracy using real-time job market data.
- ✅ Build a browser extension for LinkedIn scraping.