Junior Data Analyst to support the collection, organization, and quality assurance of data for a

Our banking client is seeking a Junior Data Analyst to support the collection, organization, and quality assurance of data for a large credit risk modernization program. (% Remote) [-87].

Overview:

The program is building foundational risk assessment tools, processes, and applications that align with regulatory expectations and peer financial institution practices. It supports the redevelopment of non-consumer credit portfolio models that rank-order loss given default (LGD) via facility risk ratings and probability of default (PD) via borrower risk ratings. The analyst will help ensure the data feeding these models is accurate, organized, and well documented. Team size is large (15+).

Must-Haves:

• Proficiency with Excel / Google Sheets (data entry, aggregation, basic formulas)
• Strong attention to detail with proven accuracy in data entry and data quality assurance
• Ability to follow structured processesand documented procedures accurately
• Bachelor’s degree or currently pursuing a relevant qualification (e.g., Finance, Business, Commerce, Statistics, Economics, Data)
• Clear written and verbal communication; comfortable asking questions and flagging issues early
• Documentation skills: maintaining organized records of data sources and collection activities

Nice-to-Haves:

• Banking or financial services industry familiarity
• Exposure to credit risk, loan processing, or credit administration
• Experience supporting data pipelines or troubleshooting basic data issues
• Previous co-op, internship, or entry-level data role
• Proactive learning mindset with ideas for improving data handling efficiency

Responsibilities:

• Assist with the systematic input and aggregation of data from specified sources into internal tools and templates
• Maintain organized records of data sources and collection activities
• Perform basic quality assurance checks on collected data
• Work with the team to understand business requirements and ensure data collection meets the needs of current projects
• Help troubleshoot basic data pipeline issues and suggest improvements for more efficient data handling