Data Scientist – Fraud Detection

About the role

We are looking for a Data Scientist specialized in fraud detection to design, build and deploy real‑time machine‑learning models that protect banking transactions. You will work closely with fraud analysts to turn large‑scale data into actionable detection solutions.

Key responsibilities

• Design, develop and improve ML models that run in real time on banking transaction and network data.
• Collaborate with fraud analysts to identify fraud patterns, engineer features and evaluate model performance.
• Handle the full ML lifecycle from data exploration, feature engineering, model training, tuning, deployment and ongoing monitoring.
• Work with large‑scale, real‑world datasets in a Linux (Ubuntu) environment.
• Maintain and optimise production pipelines to ensure reliable fraud detection.

Required profile

• Degree in Computer Science, Mathematics, Statistics, AI or equivalent practical experience.
• 2–5 years of hands‑on experience building and deploying ML models in production, preferably in fraud detection or financial crime.
• Experience with large‑scale banking transaction and network data.
• Strong English communication skills and ability to work both independently and in a team.

Required skills

• Python programming.
• Data manipulation with pandas.
• Machine‑learning libraries such as scikit‑learn.
• Proficiency in a Linux (Ubuntu) environment.

What we offer

• Competitive salary and bonus scheme.
• Pension plan, disability insurance and bike‑lease scheme.
• Hybrid working model (2 days in office).
• Training and development opportunities.
• Friendly, collaborative team in a knowledge‑driven environment.