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Data Scientist
Department:Tech - Data Science
Location:Berlin
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 it.