Data Analyst (Credit Risk)

Role Overview

As a Data Analyst (Credit Risk), you will support credit risk model monitoring and validation activities through data analysis, data collection, and data quality management. You’ll work with large and complex datasets from multiple source systems, transforming them into reliable data assets that enable risk modelling teams to assess model performance and support important business decisions.

What You Will Do

Analyze and translate credit risk model data requirements into effective data solutions, develop and maintain SAS programs to support data collection activities, identify, investigate, and resolve data quality issues, create and maintain technical documentation for end-to-end data processes, deliver high-quality data marts and datasets to model development and validation teams, and recommend and implement improvements to data collection and processing practices.

Why It Might Be a Fit

We’re looking for a Data Analyst (Credit Risk) who enjoys solving complex data challenges, uncovering insights, and helping drive better risk decisions across a global banking environment. You’ll collaborate with a diverse group of stakeholders across the bank while contributing to ING’s global data management strategy and agile ways of working.

Requirements

• Degree in Mathematics, Statistics, Computer Science, Data Science, Information Management, or a related field
• Experience in data analysis within banking, finance, or credit risk environments
• Strong SQL skills
• Strong SAS (4GL) programming skills
• Ability to analyze complex datasets and draw meaningful conclusions
• Strong problem-solving and communication skills
• High attention to detail and commitment to data quality
• Ability to manage priorities and deliver results in a fast-paced environment

Benefits

• A collaborative and inclusive international environment
• Opportunities to work on complex risk and analytics challenges
• Continuous learning and professional development
• Exposure to global stakeholders and banking processes
• The chance to contribute to meaningful decisions that help customers and businesses move forward

Tagged as: Data Analysis