This project analyzes Data Science salaries globally, aiming to uncover trends by experience level, job title, company size, remote work, and country.
It covers the full data analysis workflow: data cleaning, exploration, aggregation with SQL, and visualization through Tableau.
- Analyze the average salary by experience level
- Identify highest-paying job titles
- Explore how company size impacts salaries
- Compare remote vs on-site roles
- Examine salary differences across countries
- Build an interactive dashboard to visualize insights
- SQL / PostgreSQL – Data extraction, aggregation, advanced queries (CTEs, window functions)
- Tableau – Interactive dashboard visualization
- CSV Dataset – Real-world Data Science salaries
- GitHub – Version control and portfolio showcase
| Folder | Description |
|---|---|
sql/ |
SQL queries used for analysis |
tableau/ |
Tableau workbook (SALARIES.twb) |
dashboard/ |
Dashboard screenshots |
data/ |
Dataset CSV (ds_salaries.csv) |
README.md |
Project documentation |
The Tableau dashboard allows interactive exploration of:
- Salary by Experience Level
- Top Job Titles by Salary
- Salary by Company Size
- Remote vs On-site Salary Comparison
- Salary by Country
- Top Earners Ranking by Experience Level
- Senior-level roles consistently earn higher salaries, but specialized roles like ML Engineer also rank top at mid-levels
- Remote roles often pay more than on-site positions
- Some countries dominate in average salary, highlighting geographic disparities
- Smaller companies sometimes offer competitive salaries to attract talent
- Using CTEs and window functions in SQL allows ranking and percentile analysis for richer dashboard insights