N26

data scientist

In short

Data Scientist role at N26, a digital banking platform, building machine learning solutions for financial crime prevention and credit risk assessment. The position is hybrid in Berlin, requiring 2–4 years of practical ML experience, strong Python/SQL skills, and hands-on modelling expertise through deployment. The team includes data scientists, ML engineers and product managers, with mentoring of junior colleagues expected.

About N26
N26 is a digital banking platform that offers a branchless banking experience with no paperwork or hidden fees, helping people manage their banking and savings digitally.
Responsibilities
•Own well-scoped projects from data exploration and feature engineering through modelling to deployment, with guidance from senior colleagues on larger or more ambiguous problems
•Contribute to customer-facing solutions in financial crime prevention and credit risk assessment
•Collaborate with data scientists, machine learning engineers and product managers to deliver customer value
•Support junior colleagues through code reviews, pairing and knowledge sharing
•Experiment with new tech stacks and project ideas
Requirements
•Bachelor's or Master's degree focused on a quantitative discipline, such as mathematics, statistics or computer science
•Typically 2–4 years of practical experience developing machine learning solutions, including taking at least one model to production
•Hands-on experience with classification and regression models, time series analysis, and unsupervised models
•Solid understanding of model evaluation, including imbalanced data, validation strategies and calibration
•Strong Python and SQL programming skills
•Working knowledge of infrastructure such as Docker/containers, CI/CD and GitHub Actions, and ability to ship and maintain your own code
•Familiarity with deep learning concepts and at least one of TensorFlow, Keras or PyTorch
•Organised, self-motivated and able to drive projects independently while knowing when to ask for input
•English at full professional proficiency
•Collaborative, proactive and willing to learn, challenge the status quo, make an impact, and give and receive timely, direct feedback
Nice to have
•Banking industry knowledge, including regulatory and compliance topics, PD/LGD/EAD modelling, credit card fraud and anti-money laundering
•Cloud ML platforms, especially AWS SageMaker
•Familiarity with LLMs
•Early experience mentoring or onboarding colleagues
Conditions
•Competitive personal development budget, work-from-home budget, fitness and wellness membership discounts, language apps and public transportation benefits
•Premium subscription for the employee's personal N26 bank account, with subscriptions for friends and family members
•One additional day of annual leave for each year of service
•Relocation package with visa support for those who need it
•One dedicated office teamwork day each week, plus another day of choice; remote work the rest of the time. Some roles may require additional in-office presence

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