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AI & Data Science Internship at ABN AMRO

At a glance


Are you a MSc student looking for the ideal company to test and improve your skills? A place in which you can develop yourself into the Data Expert that you aim to become? Search no more! ABN AMRO offers you the possibility to work with the best professionals in the business.


The Chief Architect & Data Management department CADM has outlined 2 different assignments that you can apply for. Please choose only ONE of the assignments to apply for. Keep in mind, you only qualify for this internship if you are a MSc student who would like to write a thesis on ONE of the assignements. 

The Assignments


1. Cross-Organisation Federal Learning

For this assignment we would like to train models to use federated data and compute to help the ABN AMRO do Anti-Money Laundering between banks. Currently, this is done per bank basis, which unfortunately is not sufficient to detect fraud practices, since they often span between banks, countries and continents. To tackle the issue more effectively financial institutions must train collaboratively. Technically there are several approaches to this including linear regression, tree models and neural networks, which have been proven to work in federated learning environment. In this use-case several techniques will be leveraged:


  1. Differential Privacy
  2. Remote Execution
  3. Secure Multi-party Computation
  4. Homomorphic encryption



  • Input: Fake dataset for experimentation purposes.
  • Desired Output: A working POC with working server (ABN AMRO) and client (Third party, can be fake), where the client is able to train on the data of the server without seeing the real data of the server.
  • Requirements: Python programming experience, Deep Learning, Machine Learning


2. Measuring the performance of XAI approaches

Explaining the behaviour and decision-making of ML and AI models is becoming more urgent with the wider adoption of the technology. Regulators are thinking about restrictions they want to impose to increase the transparency of AI models. In every department of the bank where AI technology is being developed, certain level of explainability is required. The XAI working group of data scientists across the bank aims to unite and integrate different approaches to a common framework. However, we need a more in-depth investigation and analysis of the different approaches and an assessment and consolidation of the work we have been doing in the XAI group. What makes a good explanation is a vital part of providing an justification to the ML model’s behaviour. The ‘goodness’ of the explanation could be impacted by the use-case at hand and the type of users. We want to design an approach which will be most broadly applicable to as many users as possible.


  • Input: one (or potentially two) use cases will be identified to analyse the ‘goodness’ of explainability and how appropriate it is for different key stakeholders of the model
  • Desired Output: evaluation metric/scheme of (a few promising) explanation approaches
  • Requirement: python (desired), or R (alternative)
Your Working Environment


The DS-CoE-CADM team is positioned as a bank-wide Centre of Expertise for Data Science within CADM. The team provides additional expertise to other data science teams across the bank and delivers a wide variety of use cases. The team consists of 17 data scientists with diverse academical backgrounds and expertise in a machine learning related subjects. It’s a multicultural team with diverse nationalities. Member’s expertise include Computer Vision, Natural Language Processing, Automated Speech Recognition, Deep Learning, and Network Analysis. The team leverages a wide variety of multimodal data, including transaction-, economic-, visual-, textual- and audio data. This is used for a wide variety of use cases, to improve the customer experience, automate decision making, detect financial crime or innovate business models.

Your Profile


  • You are a Master (WO) student.
  • Your study covers Data Analytics, Data Science, AI, Machine Learning or similar field.
  • You have affinity with Python, NLP, Machine Learning, Data Scraping.
  • You are available for a minimum of 6 months to 9 months.
  • Analytical mind: your analytical skills are well developed in order to deconstruct problems and rethink possible solutions.
  • Autonomous: you are disciplined enough to work without supervision and succeed.
  • Data affinity: you are experienced at working with data and interpreting analyses.


Benefits of working with us


  • You get a Personal coach
  • Personal laptop
  • Travel allowance
  • Compensation of 600€ MSc
  • Pass to all ABN-AMRO Networking Events


Are you ready to join us?


  • Choose one of the seven assignments above that suits you.
  • In your application present yourself briefly. Tell us WHY you are interested in both this assignment in particular and working at ABN AMRO in general. Subsequently, explain HOW you will be adding value to our team..
  • Include your CV.
  • Include your availability period


Any doubts, questions or compliments for us? Get in touch via email (it.internships@nl.abnamro.com), phone (020-3433443) or WhatsApp (+31 06 831 53373)


Please Note: If you are not an EU-resident you need a valid working permit or a standard internship agreement  if you are a non-EU/EEA student.


Amsterdam, Noord-Holland, NL

Job Posting Date: 
Requisition ID:  34083

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