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Key Responsibilities and Required Skills for SAS Analyst

💰 $70,000 - $110,000

Data AnalysisAnalyticsBusiness Intelligence

🎯 Role Definition

A SAS Analyst is responsible for leveraging SAS software to analyze, interpret, and report complex datasets to support business decisions. This role involves extracting and transforming data, performing statistical analysis, developing models, and generating actionable insights. SAS Analysts collaborate with business teams, data engineers, and management to ensure data-driven decision-making and process optimization.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Data Analyst
  • Business Analyst
  • Junior SAS Programmer

Advancement To:

  • Senior SAS Analyst
  • Data Scientist
  • Analytics Manager

Lateral Moves:

  • Business Intelligence Analyst
  • Statistical Programmer

Core Responsibilities

Primary Functions

  • Develop, validate, and maintain SAS programs for data extraction, transformation, and analysis.
  • Perform statistical analyses, including regression, ANOVA, and predictive modeling.
  • Extract data from relational databases and integrate multiple datasets for analysis.
  • Design and implement automated reporting solutions and dashboards using SAS.
  • Analyze complex datasets to identify trends, patterns, and anomalies.
  • Support clinical, financial, operational, or marketing analytics projects with accurate data insights.
  • Ensure data quality and integrity by performing thorough validation and error checking.
  • Collaborate with business stakeholders to understand requirements and define analytical solutions.
  • Document SAS code, processes, and methodologies for reproducibility and compliance.
  • Develop and maintain data dictionaries, metadata, and code repositories.
  • Perform ad-hoc analyses to address business questions or regulatory reporting requirements.
  • Implement data transformations, aggregations, and summarizations efficiently.
  • Support regulatory submissions and compliance reporting using SAS outputs.
  • Assist in designing experiments or clinical trial data analysis plans when applicable.
  • Troubleshoot and optimize SAS code for performance and accuracy.
  • Conduct exploratory data analysis to identify opportunities for business improvements.
  • Collaborate with IT and data engineering teams to optimize data pipelines.
  • Mentor junior SAS programmers or analysts in best practices and coding standards.
  • Participate in cross-functional projects requiring advanced data analysis.
  • Stay current with SAS software updates, statistical methods, and industry analytics trends.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis.
  • Contribute to the organization's data strategy and analytics roadmap.
  • Collaborate with business units to translate data needs into analytical requirements.
  • Participate in project planning and agile ceremonies within the analytics team.

Required Skills & Competencies

Hard Skills (Technical)

  • Advanced proficiency in SAS programming, including Base SAS, SAS Macro, SAS SQL, and SAS ODS.
  • Strong statistical and analytical skills for interpreting complex datasets.
  • Experience with data extraction, transformation, and loading (ETL) processes.
  • Proficiency in relational databases, SQL, and data warehousing concepts.
  • Ability to create automated reports, dashboards, and visualizations in SAS.
  • Knowledge of clinical trial data analysis or business reporting requirements.
  • Experience with statistical modeling, regression, and predictive analytics.
  • Ability to validate and troubleshoot code and analytical outputs.
  • Understanding of data governance, quality assurance, and compliance standards.
  • Experience with version control and documentation for reproducible analyses.

Soft Skills

  • Strong analytical and problem-solving abilities.
  • Effective communication with technical and non-technical stakeholders.
  • Attention to detail and accuracy in data analysis and reporting.
  • Ability to work collaboratively in cross-functional teams.
  • Time management and organizational skills for handling multiple projects.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor’s degree in Statistics, Mathematics, Computer Science, Data Science, or related field.

Preferred Education:

  • Master’s degree or professional certification in Data Analytics, Biostatistics, or related discipline.

Relevant Fields of Study:

  • Statistics
  • Mathematics
  • Data Science
  • Computer Science

Experience Requirements

Typical Experience Range:

  • 2–5 years of experience in SAS programming and data analysis.

Preferred:

  • Experience in clinical, financial, or operational analytics projects using SAS.
  • Proven track record in developing automated reporting and statistical models.
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