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Internship - Merchant Monitoring

Posted 27 May 2026
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Work experience
0 to 1 years
Full-time / part-time
Full-time
Job function
Degree level
Required language
English (Fluent)

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At Mollie, the Financial Crime Monitoring team is exploring how visual pattern recognition can help identify suspicious behavior more quickly and accurately than traditional text-based assessments.

Thesis Intern: Behavioral Science & Visual Analytics in Financial Crime

The mission: Can we spot money laundering as instinctively as a baby chick spots a predator? Join us to find out.

In the Financial Crime Monitoring team at Mollie we are drowning in text but searching for patterns. Currently, our analysts spend hours reading through transaction logs, internal databases and online sources to identify suspicious behavior. We want to flip the script.

We are looking for a motivated Master’s student to research the psychology of visual pattern recognition, such as z-glyphs and other non textual representations. Our aim is to see if we can detect financial crime faster and more accurately than through traditional charts and text only based assessments.

Key Research Questions

  • Cognitive Load: Does transaction and merchant/consumer data represented as a z-glyph (or similar) reduce the mental energy required to identify suspicious or anomalous patterns?

  • Speed vs. Accuracy: Can an analyst spot a Money Laundering or Terrorism Financing typology in a visual icon faster than they can read it in various sources of text without losing precision?

  • Human in the loop: How do different visual encodings (color, stroke weight, shape) affect the psychological confidence of a Financial Crime investigator?

  • Explainability: Design a controlled mechanism that proves all data, both through text and image, is explainable and useful in context wrt discussions with supervisory bodies such as DNB (De Nederlandsche Bank).

  • UX/UI: How can we best display the various data types into images? What would these images look like and what are the differences between images in terms of accuracy?

  • Skill requirement: To what extent is the displaying and assessing of the image dependent on the background knowledge of the person with regards to ML/TF?

What You Will Do

  1. Literature Review: Explore the intersection of Gestalt principles, preattentive attributes, and visual analytics in high stakes decision making.

  2. Experiment Design: Design and create a controlled A/B test environment where participants assess simulated cases using text based logs vs. visual z-glyphs (or similar).

  3. Data Analysis: Quantify the time to decision and error rates between both groups.

  4. Prototype Feedback: Work with our monitoring team to iterate on how these glyphs should look in a real world dashboard.

Who You Are

  • Currently enrolled in a Master’s program in Psychology, Cognitive Science, Data Visualization or a similar field.

  • You are fascinated by how the human brain processes information and want to apply that to catching the bad guys.

  • Experience with experimental design and statistical tools such as SPSS, R, or Python. A basic understanding of UX/UI principles is a strong plus.

What’s In It For You?

  • Real World Impact: Your research will directly influence the next generation of our internal monitoring tools.

  • Expert Access: Work alongside seasoned financial crime investigators, senior engineers and data scientists.

  • Data Access: We provide the data and the environment; you provide the brainpower.

  • Tools: We will provide you with a MacBook.

Benefits

  • Noise cancelling headphones

  • MacBook

  • Birthday off

  • Complimentary baby days

  • 20 days working from abroad

  • 22 holiday days

  • Internet allowance

  • Lunch voucher

  • Wellbeing program

  • Health insurance

  • Bonus scheme

  • Equity plans

  • Referral bonus

  • Learning platform

  • Mentor program

  • Work from home budget

  • 25 holiday days

  • Bike lease plan

  • Pension plan

At Mollie, we’re on a mission to make payments and money management effortless for every business in Europe.
We started 20 years ago when we launched a more affordable way for companies to get paid. That provided an alternative to the frustrating, overpriced solutions that banks offered at the time. Today, we serve more than 250,000 businesses across Europe with an all-in-one solution that simplifies payments and money management.

Finance & Banking
Amsterdam
Active in 12 countries
670 employees
50% men - 50% women
Average age is 34 years