Requirements

• Bachelor’s or Master’s degree with a focus on quantitative disciplines including mathematics, statistics, or computer science.
• Practical experience (2–4 years) developing machine learning solutions, with at least one model taken to production.
• Hands-on experience with a range of modeling techniques.
• Solid understanding of model evaluation, programming skills in Python and SQL.
• Working knowledge of infrastructure (e.g., Docker/containers, CI/CD).
• Familiarity with Deep Learning concepts and at least one framework.
• Organized, self-motivated, and strong language skills in English.

Nice to Haves

• Knowledge of the banking industry.
• Experience with cloud ML platforms, especially AWS SageMaker.
• Familiarity with Large Language Models (LLMs).
• Early experience mentoring or onboarding colleagues.

What You'll Be Doing

• Own well-scoped projects from data exploration to deployment.
• Contribute to financial crime prevention and credit risk assessment solutions.
• Collaborate with cross-functional teams to deliver customer value.
• Support junior colleagues through code reviews and knowledge sharing.
• Experiment with new tech stacks and project ideas.

Perks and Benefits

• Accelerate career growth with a disruptor in Europe.
• Competitive personal development budget, work from home budget, and more.
• In-office teamwork days and remote work flexibility.
• Premium N26 bank account subscription for employees.
• Additional annual leave day for each year of service.
• Autonomy, cutting-edge technologies, and a diverse team.
• Relocation package with visa support.