Wholesale Banking Model Data Analyst Expert

Description

ING Hubs Poland is hiring!

Nr ref.

• REQ-10116393

Spółka

• ING Hubs

Kategoria

• Data Science

Lokalizacja

• Warsaw, Poland

Data publikacji

• 12/06/2026

Poziom stanowiska

• Professional

Your responsibilities

• data analysis and data delivery for Wholesale Banking portfolios,

• data processing, data quality assessment, and all other tasks related to data,

• writing efficient SAS macros programs,

• finding discrepancies in the data and proposing solutions to the problems by conducting various analyses in 4GL/SQL,

• conducting Data Quality Tests,

• gathering requirements regarding modelling datasets from our stakeholders,

• creating documentation related to the data (Data Plans and other data documentation required for Model Life Cycle),

• checking with Model Owners/Model Developers/Validators whether all the assumptions in the created datasets are in line with their expectations.

You will get extra points for

• experience working in a bank, financial institution or other institution regulated by the government,

• knowledge about credit risk models (PD, LGD, EAD, IFRS9, IRB),

• working in Agile environment, and knowing how to make it a real part of your job,

• experience with GIT or other version control systems.

We are looking for you, if you

• would like to support Wholesale Banking Model Data Team with insight about data and credit risk methodologies,

• would like to work with other Analysts from all over the world on understanding the data, IRB/IFRS9 models and portfolio specifics,

• would like to define how the data process flow for Model Development / Model Monitoring / Model validation should look like,

• have experience in gathering and analyzing data requirements and, based on them, preparing the data,

• have min. 5 years of experience working in the area in data analytics or data science,

• have min. 5 years hands-on experience working with SQL and/or SAS (preferably SAS Enterprise Guide),

• are able to define problems, analyze key information and make connections, in order to find appropriate solutions.