LinkedIn Job Search Dashboard

My Role

Cleaned and transformed raw job data using both Python (Pandas) and Power BI (Power Query).

Created calculated columns and measures using DAX in Power BI.

Built an interactive dashboard with slicers, charts, and KPIs in Power BI.

Developed visualizations and performed exploratory data analysis (EDA) in a Google Colab notebook.

Interpreted insights to support decision-making for job seekers and recruiters.

Data Preparation & Cleaning

Power BI:

Job Categorization: Created a new column job classifying titles into 5 categories: Data Analyst, Data Engineer, Data Scientist, Machine Learning & AI, and Other.

City to Country Mapping: Extracted and cleaned city data into a new country column.

Salary Extraction: Parsed salary information from the description column into a new salary column.

Custom DAX Measures: Created KPIs like total jobs, average salary, job frequency, and salary range by role.

Python (Colab):

Used Pandas for data cleaning and transformation.

Visualized job data using Matplotlib and Seaborn.

Focused on similar tasks: cleaning description, creating job and country columns, and visualizing job and salary distributions.

View the Colab Notebook:

Google Colab - LinkedIn Job Analysis

Key Metrics

Total Jobs: 327

Unique Job Titles: 5

Average Salary: 156.22K

Unique Hiring Companies: 193

Most Frequent Job Title: Data Analyst (170 postings)

Key Insights

High Market Demand:

Data Analyst jobs make up over 51% of listings.

Top Hiring Regions:

USA, India, and UK dominate the job market.

Salary Insights:

Data Engineers earn the highest salaries.

AI/ML roles are highly compensated.

Trend Analysis:

Most jobs were posted earlier in the year, showing a potential seasonality in hiring.

? Recommendations & Actions

Job Seekers:

Focus on tools like SQL, Python, and Power BI.

Apply to companies in high-posting countries.

Recruiters:

Benchmark salaries, especially for engineering and AI roles.

Educators:

Enhance curriculums focused on high-demand skills.

Tools & Technologies

Power BI: Visualization, DAX, Power Query

Google Colab (Python): Pandas, Matplotlib, Seaborn

Excel/CSV: Source Data

Project Files

LinkedIn_Job_Dashboard.pbix – Power BI dashboard

linkedin_job_analysis.ipynb – Colab notebook (link above)

Cleaned dataset with new columns: job, country, salary """