Description

You will analyze large-scale transactional datasets to detect and mitigate complex gift card fraud schemes.

Responsibilities

• Analyze large-scale transactional and behavioral datasets using PySpark to uncover emerging fraud patterns and anomalies.
• Design and implement scalable fraud monitoring solutions and dynamic prevention strategies in collaboration with Fraud, Legal, Operations, Product, and Business Development teams.
• Develop and maintain dashboards and reports to monitor suspicious activity trends and fraudulent behaviors.
• Create and track fraud-specific KPIs to measure and optimize the effectiveness of prevention initiatives.
• Partner with data scientists and engineers to build and refine fraud prevention tools and monitoring systems.

Required Skills

• 6–9 years of hands-on experience with PySpark, including large-scale data processing and ETL workflows.
• Demonstrated experience in fraud detection, specifically regarding gift card fraud.
• Strong proficiency in data analysis, pattern recognition, and statistical modeling.
• Experience collaborating with cross-functional business and technical teams.
• Ability to communicate analytical findings clearly to both technical and non-technical stakeholders.
• Any Graduate degree.

Preferred Skills

• Proficiency in SQL and Hadoop for data extraction and manipulation.
• Experience developing dashboards and reports using BI tools such as Tableau or PowerBI.
• Familiarity with building or evaluating machine learning models for fraud detection.

Key Skills

Education

Any Gradute