Master thesis project: Evaluating Fairness Interventions in Machine Learning

Research goal

As machine learning systems are increasingly used to support decision-making, ensuring fair outcomes has become an important challenge. This thesis will investigate and compare different approaches for mitigating unfairness across the machine learning lifecycle, including data preparation, model development, and prediction adjustment stages.

The research will assess how various fairness interventions affect both model performance and fairness metrics, using representative datasets and practical use cases. The objective is to provide insights into the strengths, limitations, and trade-offs of different techniques, and to develop recommendations for the responsible design of machine learning systems.

Context

At the ING Analytics department we make many types of model predictions about retail and corporate clients where fairness is important and taken into account.

The team

The Wholesale Banking Advanced Analytics (WBAA) department 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.

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.

How to succeed

This project is suitable for students interested in machine learning, responsible AI, algorithmic fairness, and applied data science.

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.

To take on this challenging and rewarding opportunity, you’ll need to: 

• 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

What do 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 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.