We are seeking a skilled developer to create a high-volume, repeatable solution for scraping LinkedIn profiles. The primary goal is to extract thousands of profiles based on custom search queries.
Key requirements for the solution include:
- Ability to extract data from a large number of LinkedIn profiles (targeting 10,000+ profiles per run).
- Repeatable execution, allowing the tool to be run daily or weekly without issues.
- Implementation of robust anti-detection mechanisms, such as rotating user agents, proxies, and random delays, to prevent blocking.
- Automatic detection and removal of duplicate profiles across multiple runs (based on criteria like profile URL, email, or name).
- Export of extracted data in a clean, structured CSV format.
- A simple and user-friendly interface for defining search queries and managing runs.
The technical approach is open to the freelancer's expertise (e.g., Python,
Node.js, APIs, or other creative solutions).
Deliverables:
- A fully functional script, tool, or application.
- A sample output file containing data from at least 1000 test profiles.
We are open to discussing the budget based on the proposed solution's quality and capabilities.
In your proposal, please:
- Describe your proposed scraping approach.
- Share examples of similar high-volume scraping projects you have completed.
- Confirm your ability to handle automatic deduplication.
- Provide realistic estimates for the volume of profiles that can be scraped per run.
Plazo de Entrega: No definido