Analysis of Cybersecurity job roles and salaries, utilizing a comprehensive dataset to evaluate market trends and salary distributions across different geographic locations and experience levels. As a Data Science Master's student preparing to enter the job market in 2023, this analysis is particularly aimed at identifying lucrative roles and key locations for Cybersecurity professionals.
Conducts a thorough examination of the Cybersecurity roles and their corresponding salaries, highlighting which roles are the most compensated.
Analyzes the distribution of jobs and their salaries across different locations, with a focus on identifying the regions with the highest number of opportunities.
Compares average salaries across different experience levels from entry-level to executive roles, providing insights into career progression and potential earnings.
Utilizes advanced visualization tools like Plotly to represent data through interactive charts and graphs, enhancing the understanding of trends and outliers.
- Python
- Data Analysis
- Plotly and Seaborn for Visualization
- Pandas for Data Manipulation
- Statistical Analysis
- Pandas
- Expand Data Sources: To enhance the accuracy and robustness of the analysis, additional data sources could be integrated, such as real-time job market data and more granular location-based salary information.
- Predictive Analytics: Implement machine learning models to predict future salary trends based on current and historical data.
- Real-Time Dashboard: Develop a real-time interactive dashboard that updates with the latest job openings and salary trends in the Cybersecurity field.