Internship - Master thesis project in: ModernBERT for Entity Matching

As the largest bank in the Netherlands ING sees the majority of all payments made by Dutch entities. People and businesses interact by making payments to each other. Salary payments, payments for rent, utilities, groceries, payments for materials, services, resources. Through billions of payments, the millions of entities form a large network. Of our own clients, entities that have an account with ING, we have information, but for accounts at other banks that send payments to or receive payments from ING accounts, we generally do not. We would like to use the payments sequences that accounts at other banks send to or receive from ING accounts, to distill information about the account holders.
Wholesale Banking Advanced Analytics department (WBAA) at ING provides data analysis and data science solutions for the bank's Wholesale banking branch.

Entity Matching is one of the fundamental data science challenges within financial institutions. In many operational processes, we need to be able to link companies in a dataset to our own client base, rapidly and often at scale. For instance, this could involve matching a dataset of companies involved in money laundering published by a journalism collective, a dataset with external CO2 emissions for clients and their suppliers, or names in transactions, to our clients.

This problem is challenging due to:
1.) The naïve solution of comparing all records being too computationally complex in practice, (e.g. O(n*m) could take months or years for large datasets).
2.) The information available for companies differs and is noisy.

The team
The amazing team of data scientists at Wholesale Banking Advanced Analytics has solved this problem at scale, and the first in the world to open-source our solution. See https://github.com/ing-bank/EntityMatchingModel.

At the same time, exciting developments in GenAI are making it possible to explore more contextually expressive methods, e.g. ModernBERT (https://arxiv.org/pdf/2412.13663) We are interested to see if – together with you – we can beat our previous solution! If so, we will try to publish this at an academic conference.

You will perform literature research for additional techniques. You will compare promising new entity matching techniques, how accurate they are, and how robust they are in our setup.

WBAA is a large team of data scientists, data engineers, software developers and many more, that are focused on bringing data, machine learning and statistical modeling into the products that we build for our clients or internal users. The data scientists in WBAA furthermore have a strong desire to keep up with and be part of the latest developments in the fields of AI, tooling and statistics. Which they do by working closely together with master’s students on a variety of topics to solve academic yet practical problems.

How to succeed
We hire smart people like you for your potential. Our biggest expectation is that you’ll stay curious. Keep learning. Take on responsibility. In return, we’ll back you to develop into an even more awesome version of yourself.

Our team has extensive experience with student supervision. Are you a master’s student looking for a thesis project and are you interested in this one?

Do you furthermore

• Have solid experience with Python?
• Have machine learning experience?
• Have solid skills in statistics and linear algebra (matrix rank, singular values, matrix decomposition, …)?
• Get at least six months to do your thesis project?
• Aim to go for a publication?
• Bring good vibes to your fellow data scientists?

Then we offer a master thesis project, a compensation of 700 euros per month, close supervision, and a tight community of data scientists to interact with and learn from.

Rewards and benefits

This is a great opportunity to train with highly skilled people who are experts in their field. You’ll do a lot and learn a lot – not only about your specialist area and the bank, but also about yourself and whether this type of environment is right for you.

You’ll also benefit from:

• Internship allowance of 700 EUR based on a 36 hours work week.
• Your own work laptop.
• Hybrid working to blend home working for focus and office working for collaboration and co-creation.
• Personal growth and challenging work with endless possibilities.
• An informal working environment with innovative colleagues.

During the duration of your internship at ING, it is mandatory to be enrolled at a Dutch university (or EU-university for EU passport holders).
 

Questions?
Contact the recruiter attached to the advertisement. Want to apply directly? Please upload your CV and motivation letter by clicking the ‘Apply’ button.

About our internships

Every year, more than 350 students join our internship program. While there are no guarantees about your future, many of our former interns move into a permanent role or onto our International Talent Programme (traineeship).

Whatever happens, an internship at ING is the ideal opportunity to meet a wide variety of people, to build up your own network, and to learn about many different aspects of banking – put simply, it’s a great start to your career.