PFE | Data Quality & AI | Agile data-quality playbook for Abacus migrations, augmented by AI

At Regnology our greatest asset is our people. We value diversity and foster an inclusive environment that supports learning, safety, and growth. By investing in our team, listening to customers, and encouraging creativity, we drive continuous innovation and improvement.
We offer a flexible, innovative environment where your ideas matter and your career can thrive.
Regnology is a global leader in regulatory reporting, helping financial institutions, regulators, and tax authorities improve data quality, efficiency, and cost savings. Our mission: to safeguard financial markets through smarter, future-ready solutions.

Project

Agile Data-Quality Playbook for Abacus Migrations, Augmented by AI

Project Description

This internship offers an opportunity to develop a standardized methodology for assessing data quality and migration readiness when transitioning from legacy reporting systems to Regnology's Abacus360 Banking platform.

You will gain practical experience in data profiling, validation, AI-based anomaly detection, and migration-risk analysis. You will also explore how AI can help identify data inconsistencies, prioritize potential issues, and improve the reliability of data migrations.

Responsibilities

During this internship, you will have the opportunity to:

- Develop a reusable data-quality playbook for assessing legacy data before migration to Abacus360 Banking.
- Analyze datasets to identify missing values, duplicates, inconsistencies, and invalid records.
- Define data-quality rules and validation procedures.
- Explore AI-based anomaly detection to identify unusual data patterns and potential migration risks.
- Investigate how data issues may affect migration activities and regulatory reporting.
- Apply Agile principles to organize tasks, track progress, and incorporate feedback.
- Create reusable documentation, validation guidelines, and migration-readiness checklists.
- Collaborate with team members to validate the methodology and identify opportunities for improvement.

Why we should decide on you

We are looking for a motivated final-year student pursuing a degree in Computer Science, Data Analytics, Data Science, Information Technology, or a related field, with an interest in data quality, artificial intelligence, and financial technology.

Academic background

- Final-year student in a relevant technical degree.
- Interest in data analysis, data management, or artificial intelligence.
- Basic understanding of data-processing concepts.

Skills and Qualities

- Strong analytical thinking and problem-solving skills.
- Attention to detail and a structured approach to tasks.
- Interest in data quality, AI, and data migration.
- Good communication and teamwork abilities.
- Proactive mindset and willingness to learn.

Previous experience in data analysis, AI, or regulatory reporting is an advantage but not mandatory.

Recruitment Process

- HR Interview: Discussion of your academic background, motivation, communication skills, and interest in the internship.
- Technical Interview: Assessment of your analytical thinking, problem-solving abilities, understanding of data-quality concepts, and motivation to learn about data migration and regulatory technology.

If you are eager to explore the intersection of banking, data quality, and artificial intelligence, this internship offers an opportunity to develop your skills in an international professional environment and gain valuable insight into financial regulatory reporting and data migration.

Apply now!