Senior Risk AI Data Scientist - GenAI, RAG & Credit Modelling

ING Hubs Romania; Amsterdam; Hybrid; EUR 90,000 - 150,000; Full time

Benefits offered by this job

Vacation days

Pension scheme

13th month salary

Holiday payment 8%

Hybrid working

Personal growth

Innovative colleagues

Job summary

ING is seeking a Risk AI Data Scientist to drive the integration of advanced AI capabilities into the bank’s risk management framework, including credit risk models, governance and deployment. You will build and evaluate GenAI solutions, design retrieval‑augmented generation pipelines, handle unstructured data, and ensure production‑quality, auditable workflows on GCP and Azure DevOps.

Collaborating with Integrated Risk and the Bank-wide Credit Risk Models teams, you will translate complex risk

Qualifications

• Master’s degree in mathematics, economics or equivalent.
• 7+ years of experience in risk management, with risk modelling preferred.
• Strong programming in Python and data science toolkits.
• Experience with GenAI, NLP and risk governance practices.

Responsibilities

• Develop custom models by fine-tuning open‑weights models on GCP GPUs.
• Evaluate and monitor GenAI systems for risk management use cases.
• Architect Retrieval‑Augmented Generation (RAG) pipelines for policy documents and regulations.
• Build NLP pipelines to extract signals from unstructured text and convert into features.
• Write clean, modular Python code in Azure DevOps ensuring reproducibility and deployment readiness.
• Align AI solutions with risk-domain model suites across locations.

Skills

Python

SQL

PyTorch/TensorFlow

NLP

Education

Master’s degree in mathematics, economics or equivalent

Tools

SAS

Google Cloud Platform

Azure DevOps

Job description

ING is seeking a Risk AI Data Scientist to drive the integration of advanced AI capabilities into the bank’s risk management framework, including credit risk models, governance and deployment. You will build and evaluate GenAI solutions, design retrieval‑augmented generation pipelines, handle unstructured data, and ensure production‑quality, auditable workflows on GCP and Azure DevOps.

Collaborating with Integrated Risk and the Bank-wide Credit Risk Models teams, you will translate complex risk