Risk AI Data Scientist

ING Hubs Poland; Warszawa; On-site; PLN 145,080 - 245,520; Full time

Job summary

ING Hubs Poland is seeking a Risk AI Data Scientist to drive the integration of advanced AI into the bank’s risk management, including credit risk model maintenance.

The role focuses on designing, deploying, and monitoring GenAI systems, fine‑tuning models on GCP GPUs, and building RAG pipelines with unstructured data to support risk governance across ING locations.

Qualifications

• Master’s degree in mathematics, economics or equivalent.
• 7+ years experience in risk management (experience with risk modelling is a plus).
• Advanced Python, SQL, PyTorch/TensorFlow; SAS is an advantage.
• Experience with 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.
• Google Cloud Platform (Vertex AI, Workbench).
• Strong experience with Azure DevOps (Git, Pipelines).
• Experience with end-to-end pipelines (data → model → deployment).

Responsibilities

• Develop custom models by fine‑tuning open‑weights models (e.g., Llama, Mistral) on GCP GPUs to understand the risk management nuances in wholesale/retail banking, credit policies, and financial risk.
• 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).
• 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 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.

Skills

Python

SQL

PyTorch/TensorFlow

HuggingFace

LangChain

LlamaIndex

RAG pipelines

Data governance

Data wrangling

Model deployment

Education

Master’s degree in mathematics, economics or equivalent

Tools

Google Cloud Platform

Vertex AI

Azure DevOps

Git & Pipelines

Job description

ING Hubs Poland is hiring!

The expected salary for this position: 13,000 – 22,000 PLN. The financial ranges specified in the announcement are adjusted and may differ from the range specified in the remuneration regulations.

We are looking for a Risk AI Data Scientist to drive the integration of advanced AI capabilities into the bank’s overall risk management, including credit risk model maintenance.

We Are Looking For You, If You Have

• Master’s degree in mathematics, economics or equivalent.
• 7+ years experience in risk management (experience with risk modelling is a plus).
• Advanced Python, SQL, PyTorch/TensorFlow; SAS is an advantage.
• Experience with 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.
• Google Cloud Platform (Vertex AI, Workbench).
• Strong experience with Azure DevOps (Git, Pipelines).
• Experience with end-to-end pipelines (data → model → deployment).

You’ll Get Extra Points For

• Experience working in Agile/Scrum teams.
• Knowledgeable on AI (risk) governance.

Your Responsibilities

• 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.

Information About 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 group‑wide, managed and developed centrally and consistently applied across all ING’s locations.

The role naming convention in the global ING job architecture will be “Data Scientist IV”.