Remote Production ML Scientist: Banking & Risk

N26 Inc.; Barcelona; Hybrid; EUR 60,000 - 90,000; Full time

Benefits offered by this job

Premium bank account

Remote work flexibility

Relocation visa support

Job summary

N26 Inc. is seeking a Data Scientist to build production-ready ML applications that enable customer-facing features.

You will own end-to-end projects from data exploration and feature engineering through modeling to deployment, with guidance from senior colleagues. You'll contribute to fraud prevention and credit risk solutions, collaborate with data scientists, ML engineers and product managers, and mentor juniors.

Qualifications

• Bachelor’s or Master’s degree in mathematics, statistics, or computer science.
• 2–4 years of practical ML experience with at least one model in production.
• Experience with a range of modelling techniques: classification, regression, time series, clustering, anomaly detection.
• Strong Python and SQL programming skills.
• Familiarity with Docker/containers, CI/CD, GitHub Actions, and basic cloud ML platforms.
• Knowledge of DL concepts (neural networks, transformers) and frameworks (TensorFlow, Keras, PyTorch).
• Organised, self-motivated, and able to drive projects with input when needed.
• Professional English language proficiency.

Responsibilities

• Own projects from data exploration to deployment with guidance from seniors.
• Contribute to financial crime prevention and credit risk modelling.
• Collaborate with data scientists, ML engineers, and product managers to deliver value.
• Support junior colleagues through code reviews and pairing.
• Experiment with new tech stacks and project ideas.

Skills

Python

SQL

Machine learning

ML models

Communication

Team collaboration

Self-motivated

English proficiency

Education

Bachelor’s or Master’s in quantitative discipline

Tools

Docker

CI/CD

GitHub Actions

TensorFlow

Keras

PyTorch

AWS SageMaker

Job description

N26 Inc. is seeking a Data Scientist to build production-ready ML applications that enable customer-facing features.

You will own end-to-end projects from data exploration and feature engineering through modeling to deployment, with guidance from senior colleagues. You'll contribute to fraud prevention and credit risk solutions, collaborate with data scientists, ML engineers and product managers, and mentor juniors.