(Senior) Quantitative Risk Analyst (Credit Risk)
About this role
Job ID: 6128
Would you like to take a central role in shaping Nordea’s credit risk modelling landscape and add real business value for Nordea? Then this opportunity is for you.
We are looking for a (Senior) Quantitative Risk Analyst to join our IRB modelling functions and drive the design, enhancement, and implementation of credit risk models across the organisation. The role combines advanced modelling, practical implementation of the models in our IT infrastructure and a sound understanding of banking. You need to enjoy working with large datasets, solve problems and find new and innovative solutions.
About our team
Meet the Risk Models Methodology & IRB models team. Our role is to develop and maintain models under IRB, and support other functions in the value chain . We strive to develop models that help business in their decisions and comply with relevant regulatory environment across multiple countries.
Our team adds value by accurately estimating the IRB risk parameters for Nordea’s customers. As the (Senior) Quantitative Risk Analyst you will play a valuable role in developing, maintaining and using models which accurately estimate Nordea customers’ credit risk and anchor these firmly in the business lines.
Given the nature of our data and regulatory requirements, we use advanced modelling techniques and big data technology. In addition to using leading techniques for modelling and data, the team’s role is general risk governance within credit risk modelling and methodology, including management of models, model implementation, data quality, documentation and model use.
Collaboration. Ownership. Passion. Courage. These are the values that guide us in how we work and how we make decisions – and that we imagine you share with us.
Main responsibilities in this role:
Develop technical tools that can be used for model development and other analysis, using tools such as Python.
Work on a subset of model lifecycle related activities like: data pipeline, data quali