Data Scientist

Our Customer:

Our customer is a product company with a set of tools for risk scoring and preventing chargeback fraud.
 

Responsibilities:

• Develop and enhance fraud detection models from concept to production, focusing on data normalization, network analysis, and risk scoring;
• Identify, analyze, and implement solutions for fraud patterns and behavioral anomalies;
• Design, build and maintain data science pipelines and fraud intelligence systems to improve detection accuracy;
• Collaborate with product, engineering, and risk teams to implement fraud prevention strategies;
• Own projects end-to-end - balancing short-term wins with long-term strategy.

Required experience and skills:

• 4+ years of hands-on experience in fraud analytics, data science, or risk modeling;
• Hands-on experience with Python;
• Strong practical proficiency in SQL, MLOps;
• Experience with fraud-related data tools;
• Proven ability in anomaly detection, and graph-based fraud detection solutions;
• Knowledge of monitoring and alerting tools (e.g., Grafana, Kibana);
• B.Sc./M.A/M.Sc. degree in Computer Science, Engineering, Math, Statistics, or other equivalent fields;
• English - Upper-Intermediate.

Would be a plus:

• Strong background in e-commerce, fintech, or payments.

Working conditions:

• Remote work;
• 5-day working week, 8-hour working day, flexible schedule;
• All public holidays are days off;
• Vacation and sick leave are covered by the company.