Model Developer Predictive Analytics
ING Nederland
Model Developer Predictive Analytics
ING NL is looking for a Quantitative Model Risk Specialist to join the Predictive Analytics team within the Integrated Risk Department. The role involves developing and managing credit risk models, including IRB/IFRS9 and credit decision models, with a focus on regulatory compliance and advanced analytics. Candidates should have 4-6 years of experience in credit risk modelling, strong quantitative skills, and proficiency in Python, SAS, and SQL.
Model Developer Predictive Analytics
ING NL is looking for a Quantitative Model Risk Specialist to join the Predictive Analytics team within the Integrated Risk Department. The role involves developing and managing credit risk models, including IRB/IFRS9 and credit decision models, with a focus on regulatory compliance and advanced analytics. Candidates should have 4-6 years of experience in credit risk modelling, strong quantitative skills, and proficiency in Python, SAS, and SQL.
Salary
Core Qualifications
Technical (Must-have)
Soft Skills
Key Responsibilities
- Develop, maintain, and enhance credit risk models for the Dutch portfolio, ensuring strong alignment with regulatory and business needs.
- Design and implement regulatory models for IRB and IFRS 9 purposes, contributing to methodological improvements.
- Analyse and interpret developments in provisions, risk costs, RWA, and arrears, translating outcomes into actionable insights.
- Build and refine credit decision and in-life management models (e.g., Early Warning Systems).
- Contribute to the integration of ESG risk into credit risk frameworks and analytics, in line with the bank-wide ESG strategy.
- Support the introduction of new products and processes by ensuring robust credit risk measurement and informed decision-making.
- Collaborate with Risk colleagues on the development and validation of credit risk policies, ensuring regulatory compliance and consistency.
- Work closely with front office, Group Risk, and Finance to align priorities and share expertise across functions.
- Partner with IT and data teams to ensure reliable data, infrastructure, and analytical environments.
- Apply advanced analytics and, where relevant, AI/ML techniques to improve modelling approaches and efficiency.
- Utilize modern tools (e.g., Python-based libraries) to enhance modelling and analytical workflows.
- Stay current on developments in data science, AI, and credit risk, and apply these in practice.
- Operate effectively within ING’s agile Way of Working (WoW).