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Data & AI adoption Intern

ING is hiring a Data & AI adoption Intern. Level rates it ; you can apply on ING.

Level's read on this job

  • On Level's scale, this role is Uses AI ●●○○: an ordinary role that requires AI tools.
  • Tools and skills the posting cites include AI agents.
  • Level classifies it as an internship.
  • Level lists 644 other open roles at ING.
  • The role was posted in the last few days.

AI in this role

ai-agents

Data & AI adoption Intern – ING Global Investment Center


📍 Work location : Amsterdam | 🕒 Fulltime (36 uur)


Your role


At ING, we believe AI should solve real problems and create tangible value. As an AI Adoption Intern in the Data & AI team of the Global Investment Center (GIC), you will help identify, design and structure the AI use cases that matter most to the business, and help build more scalable, data-driven ways of working across markets.

You will work with business stakeholders to understand what problem AI should solve, what data, knowledge and systems it needs, and how it fits into the way people already work. Together with the teams who build and run these solutions, you will turn promising ideas into clear, well-defined use cases.

The role also has a strong hands-on data side. You will work with data from across the organisation, help prepare and organise it, and turn it into insights that support better decisions.

This is not a software engineering internship. It suits someone who is analytical, comfortable with data, good at bringing structure to open-ended problems, and curious about how AI can change the way a global organisation works.


The team


The Global Investment Center is at the heart of ING's ambition to build a single, scalable investment engine across markets. To support this, the GIC brings together expertise, information and capabilities from across ING's markets, so they can be shared and used more widely.

You will join the Data & AI team, which works across the whole GIC to make this happen through better use of data, analytics and AI.

Key responsibilities

1. AI use-case design

  • Identify and structure AI use cases across the investment value chain
  • Work with business teams to define the problem, the expected value and whether AI is the right fit
  • Describe what each solution should achieve, who will use it, and what data, knowledge and systems it needs
  • Translate selected use cases into clear business requirements and help shape the GIC's AI roadmap

2. Data analysis and preparation

  • Work hands-on with data from different sources across the organisation
  • Help prepare, structure and improve the quality of data for analysis and AI use cases
  • Analyse data and translate findings into clear, practical insights
  • Build visualisations and dashboards that make information easy to understand

3. Knowledge and information for AI

  • Help understand what information AI solutions need, and what is already available
  • Contribute to organising information so AI tools can use it effectively
  • Work with subject-matter experts to make sure AI solutions meet users' needs

How to succeed


We are looking for someone who combines analytical thinking, comfortable with data and genuine curiosity about AI:

  • Currently enrolled in a Master's programme in AI, Data Science, Econometrics, Engineering, Business Analytics, Finance & Technology, or a similar field
  • Hands-on experience cleaning, structuring, analysing and visualising data, using tools such as Excel, Python, SQL or Power BI
  • A strong interest in applying AI to real business problems, beyond purely technical modelling
  • Curiosity about generative AI and AI agents, including how to judge the quality of their outputs
  • Able to bring structure to ambiguous, complex problems and take ownership of open-ended work
  • Comfortable working with people from different professional and technical backgrounds, and translating between business needs and data or AI concepts
  • Strong communication skills in English, written and spoken

What we offer

  • A front-row seat to AI and data transformation in ING's global investment organisation
  • Meaningful work on real business challenges and strategic decisions, not side projects
  • Variety: you will work across AI, data, analytics and investments rather than in one narrow discipline
  • Exposure to senior professionals across the organisation
  • Your own work laptop and hybrid working: at home for focus, in the office for collaboration
  • An informal, learning-focused environment with room to shape your own thinking and deliverables

During the internship, you must be enrolled at a Dutch university, or at an EU university if you hold an EU passport.


About our internships

Every year, more than 350 students join ING's internship programme. While there are no guarantees, many of our former interns move into a permanent role or join our International Talent Program.


Interested? Upload your CV and motivation letter via the 'Apply' button.

How we rate this

Data & AI adoption Intern at ING rates 46 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.

Classification

Uses AI. An ordinary role that requires AI tools.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agents

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. This role expects you to use AI tools as part of the job. Which ones have you used, and for what?
  3. Tell me about a time an AI tool got something wrong. How did you catch it?

Adapt your resume

  • List these exact terms on your resume: AI agents. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Put the AI tool in a bullet point about what you did, not just in a skills list. This role treats it as a required part of the job.

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