Data Scientist

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About the role

About the opportunity We are seeking a Data Scientist to build production-ready applications. Our Data Science team develops practical machine learning applications to enable innovative and customer-facing product features. In this role, you will: • 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 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. What you need to be successful (Background and Skills): • Bachelor’s or Master’s degree with a focus on quantitative disciplines including 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. • Hands-on experience with a range of modelling techniques, including: • Classification and regression models: (e.g., CatBoost, XGBoost, LightGBM) • Time Series Analysis: (e.g., ARIMA, SARIMA, Prophet) • Unsupervised Models: (e.g., clustering, anomaly detection such as Isolation Forest) • Solid understanding of model evaluation, including handling imbalanced data, validation strategies, and calibration. • Strong programming skills in Python and SQL. • Working knowledge of infrastructure (e.g., Docker/containers, CI/CD, GitHub Actions) and the ability to ship and maintain your own code. • Familiarity with Deep Learning concepts (neural networks, transformers, autoencoders) and at least one framework (TensorFlow, Keras, or PyTorch). • You are organised and self-motivated, and can drive projects forward independently while knowing when to ask for input. • Language skills: English (full professional proficiency). Preferred Qualifications & "Nice to Haves" • 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. Traits • Highly collaborative and actively help yourself (and others) be successful. • A strong passion for learning and continuously challenging the status quo. • Strong bias for action and a willingness to make an impact from day 0. • Give and receive open, direct, and timely feedback. • Think globally, act locally. What’s in it for you: • Accelerate your career growth by joining one of Europe’s most talked about disruptors. • Employee benefits that range from a competitive personal development budget, work from home budget, discounts to fitness & wellness memberships, language apps and public transportation. • Come together with your team in the office for a dedicated day of teamwork each week, plus another day of your choice, and enjoy the flexibility of remote work the rest of the time. Some roles may require additional in-office presence . • As an N26 employee you will have access to a Premium subscription on your personal N26 bank account. As well as subscriptions for friends and family members. • Additional day of annual leave for each year of service. • A high degree of autonomy and access to cutting edge technologies - all while working with a friendly team of peers of diverse nationalities, life experiences and backgrounds. • A relocation package with visa support for those who need

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