Data Analysis: Perform statistical analysis and interpret results to derive actionable insights.
Data Manipulation: Use SAS to clean, transform, and prepare data for analysis.
Reporting: Create and present data reports and visualizations.
Collaboration: Work with cross-functional teams to gather data requirements and understand business needs.
Programming: Proficiency in SAS programming, including SAS Base, SAS Macros, and SAS Enterprise Guide.
Data Visualization: Utilize tools like Tableau or Power BI to effectively present findings.
Knowledge: Knowledge of SQL and experience with database management systems.
Experience: Experience with data visualization tools to effectively present findings.
Industry Relevance: Experience in data analytics within a specific industry relevant to the organization. These roles are crucial for organizations to make informed decisions based on data-driven insights. The demand for SAS and Python skills in data analytics continues to grow, making this a promising career path for those with the right qualifications and experience.
