This project analyzes the data analyst job market, focusing on understanding top-paying skills, in-demand skills, and salary trends to help aspiring and current data professionals make informed career decisions.
The dataset contains detailed information on job titles, salaries, locations, and skills required for data-related roles. Through Python-based data analysis and visualization, this project uncovers actionable insights into the job market and highlights the optimal skills for growth.
- What are the skills most in demand for the top 3 most popular data roles?
- How are in-demand skills trending for data analysts over time?
- How well do jobs and skills pay for data analysts?
- What are the optimal skills to learn (high-demand and high-paying)?
This project was developed using the following tools and libraries:
- Python – For analysis and scripting
- Pandas – For data manipulation and preparation
- Matplotlib – For creating visualizations
- Seaborn – For advanced and styled visualizations
- Jupyter Notebook – For running code and combining notes with outputs
- Visual Studio Code – For script execution and version control integration
- Git & GitHub – For version control and project sharing
- Imported and cleaned the dataset for consistency and usability
- Converted job posting dates to
datetimeformat - Parsed skill lists for analysis
- Filtered job postings to U.S.-based roles for a more focused market study
Identified the top 5 skills for the 3 most popular data roles and visualized their demand.
Visualization:
Key Insights:
- SQL maintained consistent demand but showed a slight decline toward year-end.
- Excel demand rose sharply in the latter months, surpassing Python and Tableau.
- Tableau and Python demand remained stable but significant.
Analyzed how demand for key skills fluctuated throughout 2023.
Visualization:
Key Insights:
- SQL maintained consistent demand but showed a slight decline toward year-end.
- Excel demand rose sharply in the latter months, surpassing Python and Tableau.
- Tableau and Python demand remained stable but significant.
Evaluated salary distributions for common data roles and analyzed top-paying vs. most in-demand skills.
Visualization:
Key Insights:
- Senior Data Scientist roles offer the highest median salaries, often exceeding $600K in exceptional cases.
- Foundational skills like SQL and Excel are in high demand but have relatively lower pay compared to specialized tools.
- Advanced technical skills like GitLab, dplyr, and Bitbucket correlate with higher salaries.
Mapped skills by demand and median salary to determine the most optimal skills for data analysts.
Visualization:
Key Insights:
- Oracle stands out with the highest salary but moderate demand.
- Python, Tableau, and SQL Server balance strong demand with high salary potential.
- Core tools like SQL and Excel remain essential for broad market applicability.
Visualized optimal skills with color coding by technology category.
Visualization:
Key Insights:
- Programming skills typically align with higher salaries.
- Database skills like Oracle and SQL Server command some of the highest pay rates.
- Analyst tools like Tableau and Power BI are versatile, offering both strong demand and competitive salaries.
Through this project, I gained:
- Advanced experience with data cleaning, manipulation, and visualization
- Deeper insights into aligning skills with market trends and salary data
- Practical knowledge of crafting reproducible and scalable analyses
- Specialized skills increase salary potential, while foundational skills remain critical for employability.
- The job market is dynamic, with changing trends in skill demand.
- Building a balanced skill set of foundational and specialized skills is key to growth.
- Handling inconsistent or missing data during cleaning.
- Designing effective and clear visualizations for complex datasets.
- Balancing detailed analysis while maintaining a concise overview.
This analysis offers a comprehensive overview of the data analyst job market, providing actionable insights into the skills that drive demand and salary potential. It serves as a roadmap for skill development and a foundation for further exploration of the data job market as it evolves.