• Alwaleed Alkhdairi: Data preprocessing, EDA, report composition.
• Mohammed Abulkhail: Data preprocessing, EDA, data visualization.
• Mohammed Almalki: EDA, data visualization, insights summary.

In this project, we aimed to analyze a dataset containing employee salaries, education levels, years of experience, and other relevant factors. Our objectives were to gain insights into employee behavior, understand the factors affecting salary, and determine the best ways to achieve higher earnings.

The dataset was sourced from Kaggle and includes a comprehensive collection of salaries and years of experience along with educational degrees. The dataset contains information about various aspects of employees' backgrounds and earnings. Source data

1. Many employees completed their education after high school.
2. The majority of employees have relatively short work experience.
3. There is a general trend of decreasing work experience over the years.
4. A positive correlation between age and years of experience was observed, with similar proportions.
5. Similar proportions were also observed between salary and years of experience.
6. Employees with a high school diploma have experience ranging from a month to 3 years.
7. Those with higher degrees (PhD or master's) have experience ranging from 8 to 16 years.
8. Individuals with higher education levels tend to have higher average salaries.
9. Females with a PhD tend to have higher experience compared to males in the same education level.
10. Salary tends to increase with age for employees.

Through our analysis, we've gained valuable insights into employee behavior and salary dynamics. By understanding the relationships between education, experience, and salary, organizations can make more informed decisions to retain and attract talent. Our findings highlight the importance of educational attainment and years of experience in influencing earning potential.

For more detailed information, you can refer to our code and visualization files.