Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 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
- 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.
Details
ING Hubs Poland is hiring for a Wholesale Banking Model Data Analyst Expert. The role supports data and portfolio-related activities within the Wholesale Banking Model Data Team, which delivers end-to-end data solutions for IRB and IFRS9 projects across the full model life cycle.
The position involves working with Wholesale Banking portfolios, Rating Systems, model owners, model development teams, credit risk modelers, validators, and other stakeholders on regulatory projects. The global ING job architecture naming convention for this role is “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 by conducting analyses in 4GL and SQL.
- Conduct data quality tests.
- Gather stakeholder requirements for modeling datasets.
- Create Data Plans and other data documentation required for the model life cycle.
- Validate 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.
- Analyze ING Group data and prepare prototypes of new data structures.
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, and identify connections to find appropriate solutions.
- Interest in data, credit risk methodologies, IRB and IFRS9 models, and Wholesale Banking portfolios.
Additional qualifications:
- Experience working in a bank, financial institution, or another 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 is responsible for developing robust credit risk models embedded in the regulatory environment.
Salary
The expected salary is PLN 13,000–22,000 gross per month. The financial ranges specified in the announcement are adjusted and may differ from the ranges specified in the remuneration regulations.