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We build and scale horizontal ML capabilities that allow critical functions including Financial Crime, Credit Risk, and Core Operations to execute with absolute precision at scale.
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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
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Day 0
Early. Similar jobs usually come down between day 7 and day 57.
From 10,780 similar postings that came down. Coming down is not always a hire.
5 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
Technical & Domain Skills - Deep ML and MLOps Literacy: Hands-on understanding of predictive ML methodologies including classification, regression, clustering, anomaly detection, and ranking. This must be paired with architectural mastery of modern MLOps pipelines such as Kafka event streams, feature stores, vector databases, and automated retraining. - Analytical and Evaluation Rigor: Highly proficient in defining model performance metrics like precision, recall, ROC-AUC, and F1-score, with a clear ability to translate them into business ROI such as reduced false-positive fraud blocks or manual review cost savings.
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Yes. We’ve followed one other Lead Technical Product Manager — Machine Learning Platform job there since November 2026. It is still up.
New Data Scientist postings at the employers we follow are down 5% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
We are seeking an experienced Lead Technical Product Manager for our Machine Learning Platform within the Intelligent Operations Platforms segment. In this role, you will define the long term vision, platform architecture, and execution strategy for core Machine Learning infrastructure across N26. Your work will enable squads across the bank to automate risk assessments, prevent financial crime, and scale operational efficiency.
Our ML Platforms team serves as the central nervous system for real-time, data-driven decisioning. We build and scale horizontal ML capabilities that allow critical functions including Financial Crime, Credit Risk, and Core Operations to execute with absolute precision at scale. As a Lead Product Manager, you will drive multi-squad strategy, transforming complex predictive models into resilient, compliant, sub-second scoring systems.
N26 has reimagined banking for today’s digital world. Technology and design empower everything we do and it’s how we are building the global banking platform the world loves to use.
We've eliminated physical branches, paperwork, and hidden fees for an elegant digital experience and supreme savings. Giving people the power to live and bank their way is what gets us out of bed in the morning and inspires the work that we do.
We are headquartered in Berlin with offices in multiple cities across Europe, including Vienna and Barcelona, and a 1,500 strong team of more than 80 nationalities.
Sounds good? Apply now for this position.
We recognize that our strength lies in our people and the varied perspectives they bring to our workforce. We strive to build talented and diverse teams to drive our business success and empower our people to reach their full potential.
We genuinely welcome and encourage applications from people of all backgrounds, cultures, genders, sexual orientations, abilities, neurodiversities, and ages. We're committed to creating an inclusive workspace where everyone feels valued and respected, free from harassment and discrimination. If there's anything you need to make the application process work for you, please let us know by reaching out to candidate.exp@n26.com.
Visit our website to learn more about Diversity, Equity, & Inclusion at N26.
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Berlin
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- High autonomy to drive the ML technical agenda, working with a diverse, international team of peers. - A relocation package with visa support for those who need it. Who we are