Employee Salary Analytics: Data Cleaning, Insights & Executive Recommendations

Overview

A group data analytics project completed for a fictional Liverpool-based company whose leadership needed a clearer picture of its employee salary structure to support executive decision-making. Working as part of a team, the project combined a Python data pipeline with a joint report translating the numbers into actionable recommendations for management.

What I did

• •Reading and cleaning raw employee salary data in Python before any analysis was performed
• •Calculating the company's total salary spend, alongside total and average salary by department
• •Identifying the number of employees earning £50,000 or more, and flagging both the highest-paid employee and the highest-paying department
• •Extracting the names of the highest- and lowest-paid employees for management review
• •Building a bonus chart visualising the average salary distribution across departments
• •Co-writing a 1,200-word report presenting the Python code, calculation results, and key findings
• •Formulating a set of executive-level recommendations addressing salary structure and cost distribution across departments

Skills & tools