Used Tools & Technologies
Not specified
Required Skills & Competences
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.
SQL @ 3
Data Structures @ 3
Data Science @ 5
Hiring @ 3
Git @ 3
Data Analysis @ 3
Agile @ 3
- 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!
The expected salary for this position: 13 000 - 22 000 PLN gross.
The financial ranges specified in the announcement are adjusted and may differ from the range specified in the remuneration regulations.
As a Wholesale Banking Model Data Analyst you will be responsible for data and portfolio related topics in one of the squads in Wholesale Banking Model Data Team. The Data Team is responsible for E2E data solutions for various IRB and IFRS9 projects, covering entire model life cycle needs. Being the main point of contact for data delivery projects for Wholesale Banking portfolios will allow you to deep dive into portfolio and model specifics across different Rating Systems in Wholesale Banking domain. You will closely cooperate with model owners and model development teams on various regulatory projects in credit risk area.
You will gain knowledge about data we collect in ING Group, analyze it and prepare prototypes of new data structures that will be used further in the process. We have expertise about Rating Systems, Wholesale Banking portfolios and stakeholder needs on different model lifecycle phase. As a Wholesale Banking Model Data Analyst you will have crucial role to play in delivering high quality data to other participants of risk processes (i.e. credit risk modelers, validators and many others).
Responsibilities
- Data analysis and data delivery for Wholesale Banking portfolios.
- Data processing, data quality assessment, and other tasks related to data.
- Writing efficient SAS macros programs.
- Finding discrepancies in the data and proposing solutions by conducting analyses in 4GL/SQL.
- Conducting Data Quality Tests.
- Gathering requirements regarding modelling datasets from 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 dataset assumptions meet expectations.
Requirements
- Minimum 5 years of experience in data analytics or data science.
- Minimum 5 years hands-on experience working with SQL and/or SAS (preferably SAS Enterprise Guide).
- Ability to define problems, analyze key information and make connections to find appropriate solutions.
- Experience in gathering and analyzing data requirements and preparing the data.
You will get extra points for:
- Experience working in a bank, financial institution, or other regulated institution.
- Knowledge about credit risk models (PD, LGD, EAD, IFRS9, IRB).
- Experience working in an Agile environment.
- Experience with GIT or other version control systems.
Information about the team
Credit Risk Model Development is an international, global team (more than 400 risk experts) located in different locations in Europe (e.g., Amsterdam, Milan, Warsaw). The key responsibility is development of robust credit risk models firmly embedded in the regulatory environment.
The role naming convention in the global ING job architecture will be "Data Scientist IV".
The financial ranges specified in the announcement are adjusted and may differ from the range specified in the remuneration regulations.