Python Data Scraping - LinkedIn Entry-Level Job Data Scraping

Here's a clearer and more structured draft for your data scraper:



Instructions for Data Scraping Task

Your task is to extract specific information from job posting links. Below are the detailed requirements:

Data Points to Scrape:

1. Company Information:
- Company Name
- Company Details: Brief about the industry or type of work they do.
- Company Website
- LinkedIn Page: URL to the company’s official LinkedIn page.

2. Email IDs (3 Required):
- Find 3 individuals' email IDs from the following departments:
- Admin
- Human Resources
- Head of Sales/Top Leadership (CXO level in Sales)
- Marketing Head/Top Leadership (CXO level in Marketing)
- Founders/CEOs/Co-founders/Owners

3. Email Requirement:
- The email IDs must be professional (e.g., `name at company.com`).
- Avoid generic emails like `info@`, `help@`, `contact@`, etc.
- If available, include an alternative email ID for each person.
- All data must be unique (no duplicates).


Final Data Format:
Company Industry/Details Website LinkedIn Page Person Name Designation Email ID Alternative Email ID (if available)

Key Guidelines:
1. Accuracy: Ensure the data matches the right company and individuals.
2. Relevance: Only collect details from the specified departments or leadership levels.
3. Uniqueness: No duplicate entries; only one set of data per company.
4. Professionalism: Emails should be valid, active, and professional in format.



Delivery:
- Compile the data into a structured Excel or CSV file using the above format.
- Ensure the file is easy to navigate and filter for quality assurance.

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