Credit Risk Modelling Analyst

1 miesiąc temu

Warsaw, Polska ING Pełny etat

We are looking for you, if you:

have higher education (preferred: econometrics, quantitative methods, mathematics, physics, computer science, economics), have experience working with SAS (4GL/SAS DI/SAS EG/SAS EM), know SQL well, understand credit risk and IRB/AIRB models, can work in a team, can independently interpret requirements based on the collected information and assumptions, can and want to exchange knowledge with colleagues, take initiatives that have a positive impact on the quality and accuracy of the tasks performed, 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:

experience in modeling, validation or monitoring of credit risk models (PD, LGD, EAD, IFRS9, IRB), knowledge of other programming languages for statistical programming, ability to work in Agile / Scrum, advanced analytical skills, an independent, creative and proactive way of thinking, the ability to challenge the status quo, knowledge of techniques used in business analysis, SAS Viya, 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.

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 III”.

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