Data Scientist

Carbon Data Solutions; Barcelona; Hybrid; EUR 60.000 - 80.000; Vollzeit

Benefits dieser Stelle

Development budget

Work from home budget

Discounts for fitness & wellness

Public transportation benefits

Relocation with visa support

Diversity & Inclusion programs

Zusammenfassung

N26 is seeking a Data Scientist to build production-ready ML applications for customer-facing features from Barcelona and beyond. You’ll own projects end-to-end, collaborating with ML engineers and PMs to deliver real customer value and drive impact across the platform.

Ideal candidates have 2–4 years in ML with production models, strong Python/SQL, and familiarity with cloud and DL frameworks. Flexible hybrid work with visa-friendly relocation options supported.

Qualifikationen

• 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 in banking, fraud detection or credit risk is a plus.
• Strong Python/SQL coding and ability to ship code with Docker/CI/CD.

Aufgaben

• Own projects from data exploration to deployment with senior guidance.
• Contribute to solutions in financial crime prevention and credit risk.
• Collaborate with data scientists, ML engineers, and product managers.
• Mentor junior colleagues via code reviews and pairing.
• Experiment with new tech stacks and project ideas.

Kenntnisse

Python

SQL

Docker/Containers

CI/CD

GitHub Actions

TensorFlow/Keras/PyTorch

XGBoost/LightGBM/CatBoost

Time Series Analysis

Anomaly detection

Model evaluation & validation

English proficiency

Ausbildung

Bachelor’s/Master’s in quantitative field

Tools

AWS SageMaker

Docker

GitHub Actions

TensorFlow

Keras

PyTorch

Jobbeschreibung

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.

Who we are

N26 has reimagined banking for today’s digital world. Technology and design empower everything we do and it's how we are building the global banking platform the world loves to use.

We've eliminated physical branches, paperwork, and hidden fees for an elegant digital experience and supreme savings. Giving people the power to live and bank their way is what gets us out of bed in the morning and inspires the work that we do.

We are headquartered in Berlin with offices in multiple cities across Europe, including Vienna and Barcelona, and a 1,500-strong team of more than 80 nationalities.

Equal Opportunities:

We recognize that our strength lies in our people and the varied perspectives they bring to our workforce. We strive to build talented and diverse teams to drive our business success and empower our people to reach their full potential.

We genuinely welcome and encourage applications from people of all backgrounds, cultures, genders, sexual orientations, abilities, neurodiversities, and ages. We're committed to creating an inclusive workspace where everyone feels valued and respected, free from harassment and discrimination. If there's anything you need to make the application process work for you, please let us know by reaching out to [e-mail].

Visit our website to learn more about Diversity, Equity, & Inclusion at N26.