Master Thesis Topic AI Powered Data Migration Auditing

Largescale data migrations at NN must not only transform and clean massive datasets but also prove with full auditability that the numbers still add up. Manual reconciliation is slow errorprone and costly especially under the scrutiny of DNB audits. This thesis tackles that challenge by designing an AIsupported framework that automatically verifies numeric and provenance consistency across medallionlayer migrations (bronze silver gold). The goal is to detect and explain aggregation mismatches infer transformation impacts and produce cryptographically verifiable evidence packages from lineage graphs to signed aggregate proofs that are both humanreadable and auditready. By combining statistical analysis machine learning and provenance tracking the resulting prototype aims to deliver faster reproducible and trustworthy audit artifacts dramatically reducing manual effort while strengthening NNs compliance posture.

What you are going to do

You will develop and validate an AIpowered reconciliation framework that ensures numeric and provenance consistency across NNs medallionlayer data migrations delivering auditready proof for compliance with DNB requirements. The solution may combine statistical analysis machine learning provenance tracking and where beneficial autonomous agents to achieve its goals.

• Design methods to detect and localize aggregation mismatches after filtering cleaning and transformations

• Quantify and explain expected vs. unexpected data loss in migration pipelines

• Integrate statistical ML and provenancetracking techniques into a modular prototype optionally enhanced by agents

• Generate humanreadable and cryptographically verifiable audit artifacts (lineage graphs signed proofs anomaly explanations)

• Evaluate the framework on historical NN migrations and synthetic benchmarks to measure accuracy and auditeffort reduction

What we offer you

It is important to us that you continue to develop yourself. We give you the space and the confidence to grow in your career as well as a person. We help you with:

• Internship fee of 650- gross based on a 36-hour working week

• Plenty of training and learning opportunities in our Learning & Development Centre

• A large (international) network of colleagues who are keen to share their knowledge with you

• The autonomy to set out your own development path

Who you are

You have a strong passion for solving complex analytical challenges and applying AI technologies to improve processes in the financial and risk domains. You work in a structured way think critically and pay close attention to regulatory requirements and technical addition you bring:

• A degree or specialization in Computer Science Data Science Artificial Intelligence Econometrics or a related field

• Handson experience with Python

• Solid knowledge of statistics machine learning natural language processing and AI agent frameworks

• The ability to translate complex technical concepts into clear wellstructured documentation and actionable solutions

• Selfmotivation and independence in planning and conducting research

Who you will work with

You will be part of the Data & AI team within the CIO department a growing group of specialists who share a passion for creating impactful data and AI solutions. Our team offers plenty of room for learning and personal this project you will collaborate closely with colleagues from IT business and support departments to design and deliver AI-driven solutions for regulatory document generation.

Your employer will be NN Group an organization that offers a wide range of opportunities. You will work within the Life & Pensions business unit focusing on innovation in compliance and risk management processes.

Any questions

You can reach out to Rowena Taal Internship coordinator via

Are you unsure if you meet 100% of the requirements We encourage you to apply anyway and show us the unique value you could bring!