Market Information and Data Analytics (MIDA) - Data Quality - Intern - Summer 2027

Industry/Sector Not Applicable Specialism Data Quality Assurance Management Level Intern/Trainee Job Description & Summary

The Opportunity

As an AIT MIDA Data Quality - Intern, you will engage in projects that enhance the accuracy, completeness, and reliability of data, enabling businesses to trust their data for decision-making and reporting purposes. Within our Assurance practice, you will gain exposure to PwC's methodologies and support teams by performing basic tasks and conducting research. This role emphasizes learning and gaining exposure to professional work environments, where you will observe and contribute to the team's success.

As an Intern, you will focus on learning and gaining exposure to PwC's practices. You will support teams with basic tasks, participate in projects, and conduct research while observing professional work environments. This role encourages you to apply a learning mindset, appreciate diverse perspectives, and actively listen and communicate effectively. You will have the opportunity to gather information from various sources to analyze facts and discern patterns, contributing to your development and understanding of the business.

In this role, you will be part of a dynamic environment where each assignment presents unique challenges and opportunities for growth. You are encouraged to ask questions, take initiative, and produce quality work that adds value for clients and contributes to the team's success.

Responsibilities

• Supporting teams in data quality assurance tasks to enhance data accuracy and reliability
• Participating in data error checking processes to identify and correct inconsistencies
• Assisting in the development and implementation of data management plans to maintain data integrity
• Engaging in data profiling activities to gather informative summaries and statistics
• Collaborating with team members to manage independence processes and deliver data analytics for audit compliance
• Observing and learning from e