Heritage Research Group - Undergraduate Data Analytics Intern

The Heritage Group is a family-owned business focused on construction and materials, environmental services, and specialty chemicals. The Undergraduate Data Analytics Intern will improve the structure and documentation of HRG data and reports through Power BI dashboard development, reporting cleanup, data dictionary creation, dataset organization, and documentation, while gaining limited exposure to AI/ML tools.

What you'll do:

• Build, update, and maintain Power BI dashboards and reports
• Clean up and standardize existing reporting processes for clarity and consistency
• Develop and maintain a comprehensive data dictionary for HRG’s datasets
• Organize, structure, and document datasets to improve data accessibility across teams
• Create clear user guides, documentation, and training resources for data assets
• Support AI/ML modeling efforts with clean and well-structured data
• Participate in discussions on how structured data can enhance AI/ML outcomes
• Additional duties and responsibilities as assigned, including but not limited to continuously growing in alignment with the Company’s core values, competencies, and skills

What they're looking for:

• Required High School or Equivalent
• Required 1+ years Internship, co-op, or university research experience with data or reporting tools
• Strong proficiency with Power BI (or similar data visualization platforms)
• Understanding of data structuring, metadata, and documentation best practices
• Familiarity with databases, Excel, and reporting automation
• Strong written communication skills for documentation and user guides
• Team-oriented, self-motivated, and detail-focused
• Work is performed in an office environment and requires the ability to operate standard office equipment and keyboards. Must have the ability to lift and carry small parcels, packages and other items and walk short distances
• Preferred Bachelor's Degree Preferred rising senior pursuing a major in Data Science, Machine Learning, Information Systems, Engineering, or related field
• Exposure to AI/ML concepts preferred but not required