Startdatum 5 januari 2026
Looptijd: 1 jaar, met de mogelijkheid tot verlenging
Vaste kantoordagen: maandag en donderdag
Aantal uren: 36-40 uur per week

Geen ZZP
Kennis van NL taal niet vereist

Gespreksblokken:
Maandag 24 november:
13.00-14.00
16.00-17.00
Dinsdag 25 november:
10.00-12.00
13.00-15.00
15.00-17.00
Woensdag 26 november:
10.00 -11.00
13.00 -15.00
15.00 -17.00
Donderdag 27 November:
10.00-12.00
13.00-15.00
15.00-17.00
Graag bij het aanbieden van een kandidaat aangeven op welke van bovenstaande tijdstippen de kandidaat niet beschikbaar is voor een gesprek. Tevens inventariseren of de startdatum van 5 januari haalbaar is voor de kandidaat en of de kandidaat nog een vakantie gepland heeft in de eerste maanden van 2026.

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As a Data Scientist Insights Transaction Monitoring you provide data insights and build automated pipelines/workflows about the Rabobank transactions of 8+ million customers to your colleagues, enabling them to make data-driven decisions in catching criminals.

Preventing Money Laundering & Terrorist Financing are one of the key aspects for our society and our organisation, and as a bank we play a major role in this field. To be effective in fighting financial crime, we need smart individuals like you who get their energy from looking into data, patterns, and behaviour of our customers to uncover illegal activities. Together with the team you will be responsible for providing data insights about our current Transaction Monitoring (TM) system to enable further optimization of the system.
As you can imagine, doing this job requires both technical and analytical skills as well as visualization and communicative expertise. If done successfully, our operational analysts are able to focus on the true positive alerts – hence spend their time on truly value-adding activities. In summary, in this role you will be on the front line of fighting financial crime.

Top 3 responsibilities
• Create and improve pipelines for tuning, lookbacks and impact analyses. For these pipelines we need to combine different complex TM model components in a smart and efficient way.
• Performing analyses from start to finish: doing the intake, writing your code, visualizing the insights and presenting it back to the stakeholders.
• Designing and developing dashboards from front-end to back-end in production which enables rule tuning, rule development and getting insights in our daily detection.

Practical Examples
• Estimate the impact of proposed changes to parameters in the TM model on the efficiency of the model.
• Improving and optimizing our workflows such that our model can be tuned for even more parameter combinations.
• Build dashboards and bring them to production by collaborating with our platform squads.
Examples of dashboards we are currently working on:
- a TM rule performance dashboard such that it will be easier to optimize the rules of our TM system;
- an overview dashboard that will give more insight in our TM system;
- a transaction dashboard that can be used to develop new TM rules.

You and your talent:

Hard skills
• Have a Masters’ degree in a technical field.
• Have 5+ years’ experience performing data analysis in Python.
• Have experience with PySpark, Databricks, Power BI.

Soft skills
• Experience with building end to end solutions by using repos, version control, pipelines and a testing framework.
• Have the ability to find the real question behind a question and to present your ideas and results in a convincing way.
• Are structured, precise, communicative, pro-active, and have a business focus and can-do mentality to make the difference.
• Have experience with guiding junior and mediors in delivery/share your technical vision.
• Being able to see the bigger picture and look ahead into possible new insights