Data Scientist

October 8, 2026

Hybrid

Middle

Barcelona, Spain

Worth knowing

English is required

Description

N26 is hiring a Data Scientist to build production-ready machine learning applications within its Data Science team. The role focuses on financial crime prevention and credit risk assessment solutions that reach customers. You will own projects end-to-end, from data exploration and feature engineering to modelling and deployment, collaborating with ML engineers and product managers.

Responsibilities

Own projects from data exploration and feature engineering through modelling to deployment
Contribute to solutions in financial crime prevention and credit risk assessment that reach customers
Collaborate with data scientists, machine learning engineers and product managers to deliver customer value
Support junior colleagues through code reviews, pairing and knowledge sharing
Have the opportunity to experiment with new tech stacks and project ideas

Requirements

Bachelor’s or Master’s degree in mathematics, statistics, or computer science
Practical experience typically 2–4 years developing machine learning solutions with at least one model taken to production
Experience in banking, fraud detection, or credit risk is a plus
Classification and regression models: CatBoost, XGBoost, LightGBM
Time series analysis: ARIMA, SARIMA, Prophet
Unsupervised models: clustering and anomaly detection such as Isolation Forest
Solid understanding of model evaluation including imbalanced data, validation strategies, and calibration
Strong programming skills in Python and SQL
Working knowledge of infrastructure: Docker/containers, CI/CD, GitHub Actions, and ability to ship and maintain own code
Familiarity with deep learning concepts: neural networks, transformers, autoencoders, and at least one framework such as TensorFlow, Keras, or PyTorch
Organised and self-motivated, able to drive projects forward independently
Language skills: English (full professional proficiency)
Knowledge of the banking industry: regulatory and compliance, PD/LGD/EAD modelling, credit card fraud, anti-money laundering
Experience with cloud ML platforms, especially AWS SageMaker
Familiarity with Large Language Models (LLMs)
Early experience mentoring or onboarding colleagues
Highly collaborative with a passion for learning and open, direct feedback

Conditions

Dedicated teamwork day in the office each week plus another day of choice, remote work the rest of the time
Employee benefits: personal development budget, work from home budget, fitness and wellness discounts, language apps, public transportation
Premium subscription on a personal N26 bank account plus subscriptions for friends and family members
Additional day of annual leave for each year of service
Relocation package with visa support for those who need it
High degree of autonomy and access to cutting edge technologies

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