Fraud Investigation Analyst

About Jeeny:

Jeeny is a leading ride-hailing platform that strives to revolutionize daily commuting and transportation. Our app connects users with their preferred modes of transportation, making mobility accessible, convenient, and affordable for all.

We are a joint venture between MEIG (Middle East Internet Group), Rocket Internet, and IMENA. Since our inception, we have grown exponentially and currently operate in Saudi Arabia and Jordan.

At Jeeny, we value innovation, teamwork, and a passion for delivering exceptional user experiences. Join us in our mission to transform the transportation landscape.

About the Role:

The Fraud Investigation Analyst will play a pivotal role in identifying, analyzing, and mitigating fraudulent activities within the organization. This position requires a detail-oriented professional who can investigate suspicious activities, gather evidence, and recommend actionable solutions to minimize financial losses and safeguard the company’s reputation. The analyst will collaborate with internal and external stakeholders, ensuring compliance with regulatory standards while leveraging data-driven insights.

Responsibilities:

• Query large datasets using SQL to identify patterns, anomalies, and trends indicative of fraudulent activities.
• Automate fraud detection processes by developing SQL scripts and triggers to flag suspicious activities.
• Monitor real-time and historical data to detect high-risk transactions or behaviours.
• Conduct in-depth investigations of flagged activities by extracting and analyzing relevant data using SQL.
• Generate detailed reports and summaries from SQL queries to present findings to stakeholders.
• Document findings and evidence to build case files for internal or external use. Develop and maintain SQL-based dashboards to provide insights into fraud trends and high-risk areas.
• Work with IT and data teams to ensure data accuracy, integrity, and accessibility for fraud detection purposes.
• Suggest enhancements to fraud detection models based on data-driven insights.
• Collaborate with data engineers and BI teams to optimize database queries and improve data accessibility for fraud analysis.