Model Developer Predictive Analytics

This vacancy was originally posted on the 18th of June. ING NL is looking for a Quantitative Model Risk Specialist to strengthen the Predictive Analytics team within the Integrated Risk Department (IR). This position is aligned with GJA 16 (Scale 10) and is suited for a professional with a sound quantitative foundation who is eager to further develop within credit risk modelling. We are looking for someone with a strong analytical background and experience in IRB/IFRS9 rating models and/or Credit Decision Models (e.g. scorecards, Early Warning Systems), and an interest in the Model Lifecycle and emerging topics such as AI and advanced analytics.

The core task is to make an analytical contribution in maintaining a healthy lending portfolio in the near and far future. Your role will be to: 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).

We hire people for their potential. In this role, we expect curiosity, ownership in your scope, and a willingness to continuously develop your expertise. 4-6 years of experience in Credit Risk Modelling, including IRB, IFRS9 and/or Credit Decision models. Strong quantitative background with deep knowledge of statistical methods, combined with practical experience in data science and credit risk domains. MSc or PhD in a quantitative field (e.g. mathematics, physics, econometrics). Proven track record in developing and implementing (credit risk) models. Solid expertise in statistics and mathematical modelling. Strong programming skills, preferably in Python, SAS (Base/Macro), SQL and related tools. Experience with analytical and business tooling (e.g. SAS EG, Excel, Access, SharePoint). Experience with data sourcing, processing, and working with large datasets. Good understanding of the banking industry, lending products, and credit risk processes. Hands-on experience or strong interest in applying AI/ML techniques in risk or analytics. Experience in interacting with and advising senior stakeholders and guiding junior analysts. Strong analytical mindset with the ability to translate complex problems into practical solutions. Clear and effective communication skills, with the ability to write and report in English at a professional level.

We want to make sure that it’s possible for you to strike the right balance between your career and your private life.

Predictive Analytics is responsible for the (co-)development and management of regulatory and non-regulatory Credit Risk models with state-of-the-art modelling methods, tooling, and data processing technologies. These models are core to the success of ING and they are applied for different purposes, amongst others to determine capital adequacy, loan loss provisions but also credit decisions and in-life & problem management of loans. You will work in an Agile environment, collaborating with colleagues across Risk, Finance, Business, and IT. The role offers strong opportunities to develop your modelling, data, and AI-related skills in a practical setting.

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