Data Scientist (Fraud)

• Prototype, evaluate, and maintain machine learning models for fraud detection, including monitoring and retraining.
• Design and conduct experiments to assess the impact of fraud interventions, balancing customer experience with loss reduction.
• Analyze fraud typologies across product lines to guide prioritization and investment decisions.
• Develop and sustain anomaly detection systems to identify new fraud methods early.
• Collaborate with fraud operations, engineers, product managers, and analysts to implement fraud mitigation strategies based on model outputs.

• Degree in a quantitative field such as Statistics, Mathematics, Engineering, or Computer Science.
• At least 3 years of experience in data science, decision science, or risk analytics related to fraud, payments, or financial crime.
• Experience building and deploying machine learning models in production environments.
• Strong foundation in statistics, including experimentation, statistical inference, model evaluation, and feature engineering.
• Proficiency in Python and SQL and familiarity with the full model development lifecycle.
• Ability to work effectively in fast-paced, cross-functional teams with high ownership.
• Strong investigative skills to identify data patterns.
• Ability to communicate technical findings clearly to non-technical stakeholders.

The role offers an attractive salary, pension, health insurance, annual bonus, and other benefits.

Apply through the employer's official contact. The employer has not published a closing date.