Exploring Salary Trends by Role and Work Type in Excel (Part 1)

James Gifford
Jun 24
2 min read

Updated: Oct 10

This project explores 32,000+ job listings from 2023 to uncover salary patterns across roles, countries, and work types. Built as part of Luke Barousse’s Excel for Data Analytics course, it focuses on turning raw data into an interactive dashboard that reveals key market trends at a glance.

Data Science Salary Dashboard shows a map, job title and type with bar charts, median salary $90,000, top site Indeed, and job count 5,849.

Download Excel Dashboard

View Full Analysis on GitHub

The project emphasizes clear, structured logic (using formulas, data validation, and charts) to transform messy job data into an intuitive, interactive tool for exploring salary insights.

Excel Skills Used

Charts
Formulas and Functions
Data Validation
Dynamic Named Ranges
Drop-down Filters

Dataset Overview:

The dataset included job titles, average annual salaries, job location, and schedule type (remote, hybrid, onsite). I cleaned the data to remove incomplete records and used formulas to make the dashboard respond to user-selected filters.

Dashboard Process:

Salary by Job Title

I created a horizontal bar chart to compare salaries across common job titles. The data is sorted by median salary in descending order, making it easy to spot the highest-paying roles at a glance.

Bar chart showing salary ranges for job titles, with Data Analyst highlighted. Median salary is $90,000.

Salary by Country

I used Excel’s map chart feature to visualize salaries geographically. Countries are color-coded based on their median salary levels, helping users quickly identify regional trends.

Animated world map highlights countries in blue as a cursor moves. Various nations are pinpointed.

Filtered Median Salary Table

Using a combination of MEDIAN() and IF() functions, I built a formula that returns the median salary based on the selected job title, country, and schedule type. The inputs are controlled through drop-downs created with Excel’s data validation feature.

Table listing job titles with corresponding median salaries, ranging from $90,000 to $155,000.

Schedule Type Breakdown

To improve data quality, I used the FILTER() function to remove entries with multiple schedule types or unclear values. This made the schedule type analysis cleaner and more reliable.

Bar chart comparing salaries: Full-time, Part-time, Contractor, Temp work, Internship.

Conclusion

This project demonstrates how structured Excel models can turn large job datasets into clear, interactive dashboards. It highlights the value of using formulas, data validation, and visualization to translate raw data into meaningful market insights. These same principles carry through to more advanced analytics work.

Check out Part 2 to see how roles and skills impact salaries in data careers.