Data Analyst Intern

Location: Richmond, VA

At Exiger we work every day to make the world a safer place to do business in. Our experts and technology help clients prevent breaches, respond to risk, remediate issues and monitor activities. We are searching for people who think creatively to solve complex problems related to governance, risk and compliance thus delivering first class solutions for our corporate and government partners.

This is a 10-week long, hybrid internship opportunity with weekly onsite requirements. The internship will run June 2, 2025, to August 8, 2025.

The hourly compensation will be $25.00, based on a 40-hour work week.

What You’ll Do:

• Assist in providing data analysis and supporting the team with various tasks, ensuring high-quality and accurate work.
• Key responsibilities may include:
• Extracting and loading data from Exiger Technology.
• Organizing and cleaning data to prepare it for analysis.
• Using basic technical skills such as SQL, Excel, and Python to help improve and streamline processes.
• Providing regular updates on your work and progress.
• Identifying potential product or service issues and escalating them when necessary.

What You Need:

• A Bachelor’s degree (or currently pursuing) in Statistics, Applied Mathematics, Computer Science, or a related field.
• Some experience (internship or academic projects) with Python and SQL.
• Basic understanding of databases and data structures (RDBMS).
• Familiarity with data analysis tools (e.g., Python, R, VBA).
• Exposure to reporting and visualization tools (e.g., PowerBI, Tableau, or QlikView) is a plus.
• Some experience with data loading and transformation, ideally using Microsoft SQL Server (other database knowledge is a bonus).
• An interest in data analytics, pattern analysis, and anomaly detection.
• Strong organizational skills and the ability to prioritize tasks.
• Good communication skills with the ability to explain technical concepts to non-technical audiences.
• A curiosity to learn and a desire to understand business problems and how data analysis contributes to solving them.

#LI-Hybrid #Li-DNi