Corporate Data - Seasonal Intern

JOB SUMMARY:
The Data Analyst Intern will join our Business Intelligence team to support the transition of legacy analytics processes into modern data tools and platforms. This role will focus on converting existing SAS code into SQL, assisting with data transformation, and contributing to the creation and maintenance of Power BI reports. The intern will play a key part in helping the organization enhance its data reporting capabilities and improve access to actionable insights across healthcare operations.

KEY RESPONSIBILITIES:

• SAS to SQL Conversion:
  • Analyze existing SAS code and translate it into optimized SQL queries.
  • Collaborate with data analysts and engineers to ensure accuracy and performance of converted logic.
• Power BI Reporting:
  • Assist in building, updating, and maintaining Power BI dashboards and reports.
  • Help visualize complex datasets to support business decision-making.
• Data Analysis & Quality:
  • Perform data validation and QA on converted code and reports.
  • Identify and resolve discrepancies or quality issues in datasets.
• Documentation & Collaboration:
  • Maintain clear documentation of code conversions and report changes.
  • Work closely with cross-functional teams to gather requirements and deliver effective data solutions.
• Learning & Development:
  • Gain exposure to healthcare data structures, analytics best practices, and modern BI tools.
  • Stay current with data technologies and participate in internal knowledge sharing.

QUALIFICATIONS:

• Familiarity with SQL and interest in working with large datasets.
• Exposure to SAS and understanding of data manipulation logic (prior experience a plus).
• Basic knowledge of Power BI or other data visualization tools.
• Strong attention to detail and analytical thinking.
• Excellent communication and teamwork skills.
• Interest in healthcare data and using data to drive real-world outcomes.

EDUCATION/EXPERIENCE:

• Currently pursuing and/or recently graduated with a degree in Data Analytics, Computer Science, Information Systems, or a related field.