Internship Responsible AI & Financial Crime Detection

Details

Are you passionate about applying data science to real-world challenges that have tangible societal impact? During this internship, you will work at the intersection of advanced machine learning and financial crime prevention, tackling complex problems such as fairness, robustness, and uncertainty in predictive models. You will have the opportunity to explore cutting-edge techniques, contribute to meaningful solutions used in practice, and collaborate with experienced data scientists in a highly dynamic environment. This is your chance to deepen your technical expertise while making a measurable difference.

Responsibilities

As a Data Science Intern you will collaborate to develop top‑notch data science products to fight financial economic crimes such as money laundering, fraud and financing of terrorism. During this internship, you will contribute to one of several advanced machine learning research projects within our team, working alongside experienced data scientists for guidance, feedback, and collaboration.

At the start of the internship, you will choose (in alignment with the team) to work on one of the following topics:

• Project 1: Training machine learning models for fairness and coverage — explore how model training and decision-making can be adapted to balance predictive performance with fairness across groups and coverage across client segments, using multi-objective optimization techniques.
• Project 2: Stress testing machine learning models in the Financial & Economic Crime domain — develop methods to systematically evaluate model behavior in underrepresented data dimensions (e.g. tails of distributions) by perturbing input data, helping uncover blind spots and improve robustness. The project will also explore the use of selected synthetic scenarios as part of the training or fine‑tuning process.
• Project 3: Quantifying robustness and uncertainty in model scores — investigate techniques to estimate and incorporate prediction uncertainty (e.g., confidence intervals or distributions) into decision-making to improve reliability and reduce spurious alerts.

Working environment

Our team consists of highly skilled data scientists working on various topics. The team is internationally oriented and diverse in age, background, and education. You are expected to be able to come to the office in Amsterdam twice a week.

Requirements

• Enrolled in a Dutch university for the duration of the internship (master’s student or final-year bachelor’s student in a relevant field).
• Passion for data science, proficiency in Python, and the ability to work with (or quickly learn) PySpark are essential.
• Strong affinity with data and software engineering and preferably PySpark.
• Fluency in English.
• Available for a minimum of four months, with a flexible starting date.
• Ability to come to the office in Amsterdam twice a week.

Skills you should bring:

• Communication: convey information clearly and effectively.
• Research: hypothesize, test and compare results in a scientific way.
• Teamwork: work well with others to achieve common goals.
• Time management: efficiently manage time and tasks.
• Adaptability: adjust to new situations and challenges with ease.

Benefits

• A personal laptop.
• An internship allowance of €750 per month.
• Networking events.
• A workspace in an informal and multicultural environment among top professionals.
• And of course, a great team.

Application process

1. Apply online
2. CV selection and feedback
3. Job interview(s)
4. Possible assessment
5. Job offer
6. Congratulations on your new job!
7. Onboarding Desk

Contact

Questions? For more information, please contact the I&T Internship Office at: [email protected]