We are looking for you if you have:
- An advanced degree (PhD or Masters) in a quantitative discipline, such as Computer Science, Data Science, Statistics, Mathematics, Physics, Econometrics, Quantitative Finance or related field,
- Excellent knowledge of classic machine learning methods: supervised and unsupervised learning, classification, regression, clustering, text mining, etc.,
- Profound understanding of deep learning generative AI approaches, especially Large Language Models and their popular applications,
- Analytical skills with the ability to critically assess complex models, effectively articulate and document model risk findings,
- Minimum 5 years of professional experience in validation or development of machine learning models in a financial institution or related industry,
- English verbal and writing proficiency at C1/C2 level,
- Excellent communication skills to collaborate with cross-functional teams and present validation results to both technical and non-technical stakeholders,
- Experience writing code in Python (R, SAS or other statistical programming language), data processing and advanced visualization,
- You are results-oriented, committed to high standards and quality of work.
You'll get extra points for:
- Understanding of rule-based models as applied in the banking sector,
- Experience with the Agile way of working,
- Being enthusiastic, open-minded, communicative and a pro-active team player.
- Original hobby
Your responsibilities:
- Perform independent validation and testing of a range of GenAI and other models across global ING business lines and locations to identify weaknesses and potential risks for the business,
- Deep-dive technical review of the models assessing the conceptual soundness and appropriateness of model methodologies, data quality, and model implementation, among others,
- Ensure model compliance with regulations, internal policies and industry best practices.
- Collaborate closely with cross-functional teams including model developers, risk managers, and stakeholders to address model-related findings and promote best practices.
- Stay up to date with industry trends and regulatory guidelines, in particular related to generative AI and advanced analytics models to be able to contribute to the continuous improvement of validation methodologies, standards and automation.
Information about the Team:
Within Model Risk Management Area, we are expanding the Business and Operational Analytics Model Validation (BOAMV) Chapter part of the Global ING BOAMV Tribe, with offices in Amsterdam and in Warsaw.
Warsaw MRO&BOAMV Chapter is a fast growing, energetic, international team of highly qualified Model Risk Experts & Model Validators. The Team supports/guides global and local model communities in execution of the model life cycle activities.
The Global BOAMV is responsible for validating advanced analytics and other mostly non-regulatory models used by ING worldwide. By bringing in our technical and business expertise we assure that models are appropriate for intended use, compliant with internal policies and external regulations and their limitations are well understood by the organization.
Our goal is to ensure a strong model validation and model lifecycle landscape within ING. We strive to bring fresh ideas to life and embrace challenges in a fast changing and complex environments.
We are looking for a colleague with a talent for taking it on and making it happen, and knack for always being a step ahead.