Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 4
Audit @ 4
Communication @ 7
Compliance
Experimentation @ 4
GitHub
LLM @ 4
Python @ 7
R
SQL @ 7
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
In COO R and Risk Data Tribe we translate complex banking exposures into risk‑weighted assets and provisions, ensure regulatory compliance, and drive transformation across the Risk organization.
Within COO Risk, we are structurally redesigning the Credit Risk model lifecycle activities by embedding AI to reduce manual effort, increase efficiency, accelerate compliance, and improve model quality end‑to‑end. This includes automation across model change, remediation, data collection, documentation, validation, and monitoring processes.
To support this ambition, we are looking for a Senior Expert who will take end‑to‑end ownership of AI adoption use cases in Risk — from refining the concept, through proof‑of‑concept delivery, to controlled adoption across COO Risk.
Responsibilities
As a Senior Expert you are a domain authority and change driver. You will work hands‑on on complex AI‑enabled solutions while shaping how these solutions are scaled and embedded into business‑as‑usual risk and model‑oriented processes. You operate with significant autonomy, define direction within your scope, and influence multiple stakeholders across the organization, including Tech, Analytics, CDO and more.
As a Senior Expert, you will:
- Own and refine AI adoption use cases across the Risk model lifecycle, addressing areas such as:
- data discovery, remediation, and reconciliation,
- data collection and model code redevelopment and impact analysis,
- documentation and regulatory checks,
- model validation and monitoring activities.
- Design and build proof‑of‑concept solutions together with ING Analytics teams, using AI/LLMs where they create measurable value,
- Leverage and tune existing LLMs and tools, including Office Copilot, Github Copilot, Gemini, Claude models,
- Work hands‑on with Python, SAS, and SQL to support PoC development, testing, and evaluation,
- Translate PoC outcomes into scalable adoption approaches across COO Risk, including process design, controls, and usage patterns,
- Act as a senior point of expertise for AI adoption within Credit Risk, advising stakeholders on feasibility, risks, and value,
- Ensure solutions meet expectations for traceability, auditability, and regulatory compliance,
- Drive change across teams through expertise, influence, and clear articulation of value — without formal line responsibility.
Requirements
We are looking for you, if you have:
- Senior-level experience in credit risk, risk models, or risk process transformation within a regulated environment,
- Working knowledge of AI concepts and applications, including the ability to identify where AI, advanced analytics, or LLM-based solutions can enhance credit risk or risk process outcomes,
- Strong hands-on expertise in SAS, Python, and SQL applied to analytical or model-related processes,
- Deep understanding of challenges across the credit risk model lifecycle,
- Ability to operate independently, define direction within scope, and drive adoption,
- Strong stakeholder management and communication skills at senior level.
You’ll get extra points for:
- Proven experience delivering AI, advanced analytics, or LLM-based solutions beyond experimentation,
- Experience with model governance, validation, regulatory reviews, or audit setting,
- Experience scaling PoCs into business-as-usual solutions.