Data Scientist Marketing
bunq · Amsterdam, Noord-Holland, Netherlands · Full-time
Description
At bunq, we’re on a mission to Make Life Easy for our users by creating the most user-centric banking experience out there. Our paid marketing campaigns run on predictions about which new users will turn out to be valuable. This role makes sure those predictions are right. That’s where you come in. As our Data Scientist, Marketing, you’ll own the machine learning models that predict the value of every newly verified user and feed that value into Google Ads, so our campaigns find more users like them. If the models are off, the spend is off. AI can help you write and debug code, but it can’t build the model or judge whether the output can be trusted. That judgment is yours. Take Ownership 🚀 You’ll own the predictive models that steer our marketing spend. Here’s how you’ll do it: Build, maintain and expand the predictive models for marketing, from first idea to production, starting with the models that predict each new user’s value in their first 90 days. Hit the model quality targets within 9 months: a Spearman rank correlation of 0.50 or higher and a binary model AUC of 0.75 or higher. Keep the models running in production and monitor data and model health to find where to inter…
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Questions about this job
Where is this Data Scientist Marketing job located?
The listing places this job in Amsterdam, Noord-Holland, Netherlands.
Who is hiring?
The employer shown on the listing is bunq.
What is the salary?
The listing does not state a salary. Ask the employer about pay, overtime and payment dates before accepting.
Is it full-time or part-time?
The listing type is Full-time.
When was this job posted?
It was posted on 30 October 2026. Jobs that stay open too long are closed automatically, so apply soon if you are interested.
How do I apply?
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Do I have to pay to apply?
No. Applying on Get Mazdoor is free, and a genuine employer does not ask for money to apply or for a "registration" or visa fee before an offer. If anyone asks you to pay, do not.
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