Credit Risk Data Engineer

Details

Responsibilities

• Driving the technical activities with the team and ensuring the engines run smoothly and are compliant with the latest policy updates.
• Liaise with Credit Risk Functional Analysts and modelers and ensure that functional requirements are properly implemented.
• Understanding the complex Credit Risk Data Landscape regarding the credit risk models (PD, EAD and LGD) and Engines (DOD, etc.).
• Priority & incident management alignment: ensure that incidents are properly logged and tackled, and that appropriate communication is given to involved parties.
• Contributing to the implementation of the target tooling and data landscape: help building seamless flows and efficient tooling for the Risk family and Business tribes.
• Play a key role in the digitalization of Risk.
• Contribute to a variety of projects and be in contact with many teams within the bank.
• Experience a progressive and agile way of working, where new ideas are valued ahead of convention.
• Challenging projects, at the forefront of the new regulations.

Requirements

• Experience working in Oracle Databases, SAS Data Integration Studio and SAS Enterprise Guide.
• Strong interest and understanding for data and systems, and for regulation and technology especially the data lake architecture.
• Ability to communicate with both technical and non-technical audiences.
• Fluency in English is a must.
• Our biggest expectation is that you’ll stay curious. Keep learning. Take on responsibility.

Additional Information

• Information about the Team: The Credit Infrastructure team within Integrated Risk Management is responsible for building and maintaining batch engines for the Risk domain. The batch engines compute parameters which can be rule based (like definition of default, early warning signals) as well as parameters based on models like probability of default (PD) and Loss Given Default (LGD). The Engines must be regulatory compliant as the computed parameters has a major impact on capital calculation, risk weighted assets (RWA) and the loan loss provisions (LLP). The team also maintains the data mart responsible for the development of new models. The team also acts as a vital link between credit risk business and the Operational tribes like data management.
• The role naming convention in the global ING job architecture will be "Data Scientist III".

Extra points

• Interest in design of data marts is a plus.