Wholesale Banking Model Data Analyst Expert

at ING

📍 Warsaw, Poland

PLN 156,000-264,000 per year

SENIOR

✅ On-site

✅ Visa Sponsorship

Tech Stack
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1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

Agile @ 4 Data Science @ 6 Data Structures Git @ 4 SQL @ 6

Details

ING Hubs Poland is hiring for a data and portfolio-focused role within the Wholesale Banking Model Data Team. The team delivers end-to-end data solutions for IRB and IFRS9 projects across the full model lifecycle. The role involves working with Wholesale Banking portfolios, Rating Systems, model owners, model development teams, validators, and other credit risk stakeholders.

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

Responsibilities

Analyze data and deliver data solutions for Wholesale Banking portfolios.
Process data and assess data quality.
Write efficient SAS macro programs.
Identify data discrepancies and propose solutions through analyses using 4GL and SQL.
Conduct data quality tests.
Gather stakeholder requirements for modelling datasets.
Create Data Plans and other data documentation required for the model lifecycle.
Verify with Model Owners, Model Developers, and Validators that dataset assumptions meet their expectations.
Define data process flows for model development, model monitoring, and model validation.
Prepare prototypes of new data structures for subsequent use in the data and modelling processes.

Requirements

At least 5 years of experience in data analytics or data science.
At least 5 years of hands-on experience with SQL and/or SAS, preferably SAS Enterprise Guide.
Experience gathering and analyzing data requirements and preparing data based on those requirements.
Ability to define problems, analyze key information, identify connections, and find appropriate solutions.
Interest in data, credit risk methodologies, IRB/IFRS9 models, and Wholesale Banking portfolio specifics.

Additional advantages include:

Experience working in a bank, financial institution, or government-regulated institution.
Knowledge of credit risk models, including PD, LGD, EAD, IFRS9, and IRB.
Experience working in an Agile environment.
Experience with Git or other version control systems.

Team

Credit Risk Model Development is an international global team of more than 400 risk experts located across Europe, including Amsterdam, Milan, and Warsaw. The team develops robust credit risk models embedded in the regulatory environment.