Job Posting Explorer

Project overview

Exploring the patterns behind job-posting engagement.

An exploratory LinkedIn job-listing analysis focused on salary, job attributes and application activity. The workflow cleans and joins source tables, derives comparison measures and documents how the notebook can be reconstructed.

• Python
• Pandas
• Matplotlib
• Data Cleaning

Inside this build

• Prepared five source tables covering companies, salaries, activity, work arrangements, pay periods, seniority and timestamps.
• Derived annual salary, salary range, posting duration and a zero-safe application-to-view ratio.
• Examined salary, work arrangements, seniority, posting duration, views, applications, annual pay and conversion patterns.
• Applied IQR salary filtering and optional z-score checks for outlier exploration.
• Organised a 234-cell notebook into six sections with read-only reconstruction verification and automated tests.
• Documented the unavailable raw source tables and kept conclusions within descriptive job-listing analysis.

Source code & links