Scrape LinkedIn job postings without logging in (Python + Google Sheets)
LinkedIn shows job postings to anyone, even without an account. In this tutorial we'll collect job postings — with full descriptions, salary when shown, applicant count, seniority and Easy Apply flag — for several keywords and locations, filter out what we don't want, and monitor new jobs every day. No LinkedIn account, no cookies, no risk to your profile. Disclosure: I built the Apify Actor used…
LinkedIn permits visitors to view job postings without requiring an account. This guide outlines the process of gathering full job details, including descriptions, compensation, applicant numbers, job levels, and Easy Apply options, for specific search terms and regions. The procedure excludes unwanted results and regularly checks for new postings.
No account or cookies are required, eliminating any risk to your profile. The accompanying Apify Actor, created by the author, is free and charges $0.30 for every 1,000 jobs with complete details, running on Apify's free plan. The output includes essential data for each job listing, such as title, company, location, posting date, applicant count, salary (if visible), seniority level, job type, industry, application method, poster, description, and link.
There are three methods to utilize this tool:
1. Utilizing the LinkedIn Jobs Scraper interface without any programming knowledge. Simply select "Try for free," input keywords like "data analyst," specify the location as "United States," set the date range to "week," and limit results to 100 jobs.
2. Using multiple keywords and locations simultaneously. For instance, search for "python developer" and "data engineer" across "London," "Berlin," and "Remote" locations. Additional filters include remote or hybrid work types, mid-senior experience levels, and exclusion of intern or principal roles at staffing or recruitment companies. Each keyword-location combination generates a separate search, with duplicate entries automatically eliminated.
3. Running the tool via Python, fetching a daily list of new job postings. After installing the "apify-client" package, import necessary modules, authenticate with your APIFY token, and execute the actor to retrieve jobs posted within the past 24 hours, sorted by date, and limited to 300 results. Filter out warning rows and jobs with exactly 25 applicants.
Write the desired job details, including title, company, location, salary, applicant count, application type, and URL, to a CSV file named "new_ml_jobs.csv." Finally, print the total number of new jobs and those with 25 or fewer applicants.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
