Key Skills

Job Description

We are looking for a Risk AI Data Scientist to drive the integration of advanced AI capabilities into the bank’s overall risk management (out of which Credit risk model maintenance is one of them). In this role, you operate in the intersection of risk management practices (amongst which credit risk modelling), model lifecycle governance, and advanced AI (LLMs, NLP, Agentic workflows). You will not only build and steer these solutions; you will help design the cognitive layer of the bank’s risk management environment, turning cutting-edge AI into production-ready, compliant solutions. The team The mission of Integrated Risk is focused on providing risk identification, aggregation and insight capabilities at Group level across the various Risk domains. The team department is using those capabilities across the various risk functions, to assume a general oversight of risk governance, policies and frameworks, and to steer group-wide model and implementation activities across locations. The Bank-wide Credit Risk Models department is responsible for the management of Wholesale Banking (WB) IRB and IFRS9 and the Bank-wide Credit Risk Economic Capital models — including their development, monitoring, and advisory support to the business — in cooperation with relevant stakeholders. All the models in scope are groupwide, managed and developed centrally and consistently applied across all ING’s locations. Roles And Responsibilities What will you do? Develop custom models by fine-tuning open-weights models (e.g., Llama, Mistral) on GCP GPUs to understand the specific nuances of risk management in wholesale/retail banking, credit policies, and financial risk (exploration, production and scaling). Evaluate and monitor GenAI systems in this context (e.g. hallucinations, quality, drifting). Architect Retrieval-Augmented Generation (RAG) systems to enable interaction with internal policy documents, regulations and other documentation in different formats with high precision. Work with large-scale unstructured data (documents, PDFs, OCR) as a core part of the role. Design and implement agentic AI workflows (e.g. LangChain/LangGraph) where AI components plan, reason, and execute multi-step tasks to support risk managers. Build NLP pipelines to extract complex signals (e.g. transaction patterns, legal clauses) from unstructured text and convert them into usable features. Write clean, modular Python code in Azure DevOps ensuring models are testable, reproducible, and ready for deployment. Align with model suites across different risk domains to understand and create added value in AI-powered lifecycle management. How To Succeed We hire smart people like you for your potential. Our biggest expectation is that you’ll stay curious. Keep learning. Take on responsibility. In return, we’ll back you to develop into an even more awesome version of yourself. Education & experience Master’s degree in mathematics, economics or equivalent 7+ year experience in risk management (experience with risk modelling is a plus) Core technical stack Advanced Python, SQL, PyTorch/TensorFlow (SAS is an advantage) GenAI & data capabilities HuggingFace (Transformers, PEFT), LangChain/LlamaIndex, Vector Stores (FAISS/Vertex Search), designing and optimising RAG pipelines Experience in manipulating and governing structured and unstructured data for risk management purposes Platforms & engineering Google Cloud Platform (Vertex AI, Workbench) Strong experience with Azure DevOps (Git, Pipelines) Experience with end-to-end pipelines (data → model → deployment) Way of working Experience working in Agile/Scrum teams You understand the “You Build It, You Run It” philosophy Governance & mindset Knowledgeable on AI (risk) governance Out-of-the-box, inquisitive, strategic thinking Strong risk management mindset and technically fully mature credit risk modelling skills Strong communication skills (internally and externally), with the capability of translating complex matters into simple language “Make it happen” mentality Rewards And Benefits We want to make sure that it’s possible for you to strike the right balance between your career and your private life. Find out more about our employment conditions. The Benefits Of Working With Us At ING Include 25-28 vacation days depending on contract Pension scheme 13th month salary 8% Holiday payment Hybrid working Personal growth and challenging work with endless possibilities An informal working environment with innovative colleagues About Us Curious about how ING empowers people and businesses to move forward? Discover what we do and what we can offer you. Questions? Please visit our Frequently Asked Questions section to find some answers on questions you might have. You can also contact the recruiter attached to the advertisement. Want to apply directly? Please upload your CV and motivation letter by clicking the ‘Apply’ button.

Core Responsibilities

Develop, evaluate, and deploy AI solutions for risk management, including fine-tuned language models, RAG systems, agentic workflows, and NLP pipelines for unstructured data. Build production-ready, governed, and reproducible solutions that support risk managers and improve model lifecycle management across risk domains.

Requirements

Requires a master’s degree in mathematics, economics, or an equivalent field, plus at least seven years of experience in risk management; risk modeling experience is an advantage. Candidates should bring advanced Python and SQL skills, experience with AI and data platforms and end-to-end deployment, strong credit risk modeling and governance knowledge, and the ability to communicate complex topics clearly.

Benefits

• 25–28 Vacation Days
• Pension Scheme
• 13th Month Salary
• 8% Holiday Payment
• Hybrid Working
• Personal Growth Opportunities
• Challenging Work
• Informal Working Environment