Data Analyst

We are looking for you, if you:

• have higher education or you’re finishing your university course (preferred: econometrics, quantitative methods, mathematics, physics, computer science, economics),
• have basic knowledge of SAS (4GL/SAS DI/SAS EG/SAS EM),
• understand basics of credit risk,
• are willing to work in the banking sector,
• can independently and carefully solve given problems,
• have the enthusiasm to complete even seemingly impossible tasks,
• know English well (working in an international team on a daily basis).

You'll get extra points for: 

• (work or internship) experience in banking sector, especially in credit risk,
• knowledge of other programming languages for statistical programming and for working with data bases,
• advanced analytical skills,
• an independent, creative and proactive way of thinking,
• knowledge of techniques used in business analysis,
• SAS Viya,
• SQL,
• GIT/AZURE Dev Ops,
• Python,
• Confluence.

Your responsibilities:

• analysis of requirements for credit risk models’ implementation,
• preparation of mappings for data used in credit risk models,
• preparation of documentation describing the process of implementation and delivery of the credit risk models’ data,
• testing developed code and implemented model’s outcome,
• preparing data for the monitoring requirements,
• work on creating automatic data feeding processes,
• work on other tasks of the squad.

Information about the squad: 

Our team is responsible for the implementation of credit risk models for various business units across ING group. We are focusing on accurate representation of the models based on the received documentation and on delivering model outcomes for the purpose of models’ monitoring. We are looking for a specialist with the knowledge of risk data and credit risk models. Our team is international, and we cooperate with other teams scattered around the world. We place great emphasis on acquiring and sharing knowledge. We combine knowledge in the field of risk modeling and advanced data processing. We can also have fun and celebrate our successes after work. Each team member feels appreciated and can pursue their ambitions.

The role naming convention in the global ING job architecture will be “Data Scientist I”.