Requirements

• 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.
• 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 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).

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.

What You'll Be Doing

• Own well-scoped projects from data exploration and feature engineering through modelling to deployment.
• Contribute to solutions in financial crime prevention and credit risk assessment.
• 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.

Perks and Benefits

• Accelerate your career growth by joining one of Europe’s most talked-about disruptors.
• Employee benefits include a competitive personal development budget, work from home budget, discounts to fitness & wellness memberships, and language apps.
• 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.
• Access to cutting-edge technologies and a friendly team with diverse backgrounds.
• Relocation package with visa support for those who need it.