Data Job Trends Analysis from LinkedIn Postings
Jul
2024
Problem / Purpose
Job seekers and hiring managers often lack clear, up-to-date insight into demand trends and skill requirements across data roles. Publicly available reports are often too high-level or outdated.
Solution
Scraped 6,510 LinkedIn job postings using Python to analyze trends across data job titles. Explored demand by role type, employer industry and size, job location and work mode, seniority, employment type, pay ranges, and most sought-after skills by role. Created visuals and published a two-part Medium article highlighting actionable findings and insights for aspiring data professionals.
Key Achievements / Impact
Delivered two-part public analysis with data-backed insights into the data job market. Demonstrated the ability to independently gather, clean, analyze, and communicate complex information clearly. Article supports career planning and job market navigation.
Key Technologies / Tools Used
Python, Python (BeautifulSoup), Python (Selenium), Web Scraping, Data Analysis, Python (Pandas), Data Visualization
Role
Data Scientist
Personal Project