Senior Data Scientist
ING is hiring a Senior Data Scientist. Level rates it ; you can apply on Level.
AI in this role
ORGINAL POSTING DATE 5.5.2026
ING’s goal is to enable people to “do their thing” and empower them to stay a step ahead in life and in business. We are one of the largest banks in Europe and we continuously evolve to become one of the most innovative companies in the banking sector. The ING Analytics group is a major driving force in ING’s transformation, aimed at helping us to become a data-driven organization, where advanced analytics is at the heart of our business processes.
In our tribe COOA, we apply analytics & AI solutions for the Financial Crime & Fraud domains and create advanced analytics applications and models. These models are used to mitigate and to effectively tackle the risk of financial crime for our customers and our society, making us a safer and more compliant bank. Our group consists of more than two dozen data scientists, engineers, data analysts, and customer journey experts, working together to deliver innovative solutions in our domain across multiple countries.
What is the role we hiring for?
As we continue our growth and establishing the added value analytics bring to our domains, we seek to a senior data science profile with the right potential to:
Help creating innovative scalable data driven solutions in the space of Financial Crime Analytics. Typical problems cover areas such as imbalanced classification, outlier detection, entity resolution or network & graph applications.
Work with multiple teams to implement these solutions across the organization by assuring close alignments on the technical requirements and delivery
Adopt best practices and quality standards for developing & deploying fit-for-purpose model pipelines, addressing the requirements of the ING model governance.
Be an effective member of a model development & implementation squad, challenge the status quo and build what matters.
Actively learn about our domain, reach out to our stakeholders, and tell captivating stories with our data to create a journey that makes our bank and our society safer.
Who should apply?
At ING, we promote diversity not just because it is the right thing to do, but because it’s essential for delivering on our strategy. In order to stay a step ahead we need teams with a healthy mix of contrasting perspectives and backgrounds as they are more creative, faster to adapt and more inventive with their solutions. We strive to hire a workforce as diverse as the communities in which we operate, and we will consider every application, regardless of race, religion, color, national origin, sex, disability or age.
Qualifications
You have at least 5 years of (global) work experience in the Data Science space (methods, technology, data) including statistical modelling and machine learning experience to solve business questions and/or develop (innovative) data driven products
Experience in applying data science to prevent and detect financial crimes (e.g. internal/external fraud, money laundering, terrorism financing, tax evasion, …) is a strong plus
Scikit-learn Professional Practitioner certificate is a strong plus
You have excellent communication skills and you can explain complicated subjects clearly
You are friendly and approachable and are able to mentor junior data scientists
You are capable of working collaboratively in a semi-remote, globally distributed team.
Your enthusiasm is visible and you are good with mobilizing people for our data driven purpose
You are motivated to keep on top of the latest developments
You have extensive knowledge of a wide range of machine learning algorithms, ranging from more classical econometric models to cutting-edge neural networks and are able to match them to business problems
You are able to see where ING can set further steps towards becoming a truly data driven bank. You’re always thinking one step ahead, for example in advising about the best way of implementation.
You are a team player who strikes effective balance between independence and acting in the interest of the team
Experience
MSc or PhD with excellent academic results in the field of Data Science, Computer Science, Mathematics, Physics, Engineering, Econometrics or similar.
You have a profound theoretical understanding of Machine Learning: Classification, Outlier detection, NLP, Regression, Clustering etc. You have extensive experience with algorithms like Random Forests, Gradient Boosting, Neural Networks, Logistic Regression, SVM, KNN, K-Means, etc. Knowledge of parametric and non-parametric statistics is a strong plus.
Strong Python programming skills, including object-oriented programming, package development, working with Git. Familiarity with software engineering practices is a plus.
Experience with Apache Spark
Rewards and benefits
We want to make sure that it’s possible for you to strike the right balance between your career and your private life. https://careers.ing.com/en/benefits-NL
The benefits of working with us at ING include:
25-28 vacation days depending on contract
Pension scheme
13th month salary
8% Holiday payment
Hybrid working
Personal growth and challenging work with endless possibilities
An informal working environment with innovative colleagues
About us
Curious about how ING empowers people and businesses to move forward? https://careers.ing.com/en/working-in-the-netherlands
Questions?
Contact the recruiter attached to the advertisement. Want to apply directly? Please upload your CV and motivation
How we rate this
Senior Data Scientist at ING rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
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Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- Typical data scientist job
- $168k
This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs
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- What NLP problem have you worked on, and how did you measure whether it actually worked?
- Walk me through how you've used scikit-learn in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
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- List these exact terms on your resume: NLP and scikit-learn. An applicant tracking system matches the wording, not the idea.
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- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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