Hybrid Fraud Analytics Senior Analyst – Data-Driven Impact

Citi; Kuala Lumpur; Híbrido; MYR 100.000 - 140.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work model

Learning and development resources

Descripción de la vacante

Citi is inviting a high-caliber professional to join as Officer, Fraud Analytics Senior Analyst (Hybrid) based in Kuala Lumpur. The role focuses on developing fraud management policies, analyzing trends, and guiding loss prevention strategies with a strong emphasis on data-driven decision making.

Ideal candidates will have 2–5 years in fraud analytics, solid SQL/Excel skills, and experience with detection platforms.

Formación

• Bachelor's degree or equivalent in a related field.
• Familiarity with BI tools such as Tableau or Power BI.
• 2–5 years of experience in fraud analytics or related areas.
• Strong hands-on SQL, Excel, and at least one analytics or scripting tool.
• Experience with fraud detection platforms (Actimize, Falcon, SAS, etc.).
• Clear written and verbal communication skills.

Responsabilidades

• Provide professional analytical expertise for fraud prevention and loss control.
• Analyze fraud trends and conduct investigative research into losses.
• Perform complex data validation and recommend actions to portfolio managers.
• Resolve varied fraud issues and guide process improvements.
• Integrate specialty knowledge with industry standards and practices.
• Offer informal guidance or training to teammates as needed.
• Ensure timely and quality service to support the team and related groups.

Conocimientos

BI tools

SQL

Excel

Python/R/SAS

Fraud analytics

Communication

Educación

Bachelor's degree or equivalent (Data Science/Statistics/Finance/CS)

Herramientas

Tableau

Power BI

Actimize

Fraud detection platforms

Descripción del empleo

Citi is inviting a high-caliber professional to join as Officer, Fraud Analytics Senior Analyst (Hybrid) based in Kuala Lumpur. The role focuses on developing fraud management policies, analyzing trends, and guiding loss prevention strategies with a strong emphasis on data-driven decision making.

Ideal candidates will have 2–5 years in fraud analytics, solid SQL/Excel skills, and experience with detection platforms.