Description

MTN Uganda is hiring a Manager – Fraud Intelligence & Analytics to lead the execution of the fraud strategy and plan through proactive identification, analysis and mitigation of fraud risk across the fintech ecosystem. The role will further be responsible for delivering strategic intelligence on emerging fraud risks across all products, channels, and internal operations to safeguard the integrity and security of fintech services. The role will further partner with key stakeholders across the wider MTN Group and the industry to support forensic investigations and related preventive actions.Kampala job listings

Key Duties and Responsibilities:

• Leading the execution of the fraud strategy and plan.
• Leading fraud detection and analytical Intelligence across the Fintech ecosystem.
• Effective management of fraud detection tools and analytics platforms to ensure optimum utilization and efficiency.
• Collaboration with key stakeholders on proactive identification, incident response and investigative support.
• Oversight of fraud response plan and fraud awareness program.
• Timely reporting on insights around fraud intelligence, financial exposure and loss data to key stakeholders

Key Performance Areas:

• Successful execution of fraud strategy and plan.
• Effective early detection of potential fraud.
• Reduction in Fintech fraud losses (absolute & prevented)
• Effective identification and mitigation of control gaps.
• Effective collaboration with key stakeholders

Qualifications, Skills and Experience:

• Bachelor’s degree in Statistics, Computer Science, Data Science, Information Systems, Risk/Forensics, or a related field.
• Added advantage: CFE, CAMS, Data Analytics, SQL/Python, Financial Crime certifications.

Experience:

• Previous experience in fintech or banking fraud management, Data analytics, revenue assurance or AML/transaction monitoring.
• Hands-on experience with very large datasets using data analytical tools e.g., ACL or SQL or Advanced Excel or Python is essential.

Skills

• Decisive problem solver, best practice creator
• Culture and change champion, relationship builder, and fast learner.
• Result-oriented, operationally astute.
• Confidence to raise challenging questions and concerns when necessary.

Knowledge

• Risk Management, Internal Controls , Compliance Frameworks
• Deciding & Initiating Action
• Learning & Researching
• Ability to gauge and manage risk.
• Project Management abilities, including escalation of issues, analytical thinking and lateral creativity
• Entrepreneurial and Commercial Thinking

NB: Presentation of false academic documents and certification will lead to criminal prosecution. Any form of canvassing will lead to automatic disqualification. Should you not hear from us within fourteen (14) days from the closing date of this advertisement, you may consider your application to be unsuccessful.

Female candidates are strongly encouraged to apply.

• Leading the execution of the fraud strategy and plan.
• Leading fraud detection and analytical Intelligence across the Fintech ecosystem.
• Effective management of fraud detection tools and analytics platforms to ensure optimum utilization and efficiency.
• Collaboration with key stakeholders on proactive identification, incident response and investigative support.
• Oversight of fraud response plan and fraud awareness program.
• Timely reporting on insights around fraud intelligence, financial exposure and loss data to key stakeholders

• Decisive problem solver, best practice creator
• Culture and change champion, relationship builder, and fast learner.
• Result-oriented, operationally astute.
• Confidence to raise challenging questions and concerns when necessary.

• Bachelor’s degree in Statistics, Computer Science, Data Science, Information Systems, Risk/Forensics, or a related field.
• Added advantage: CFE, CAMS, Data Analytics, SQL/Python, Financial Crime certifications.
• Previous experience in fintech or banking fraud management, Data analytics, revenue assurance or AML/transaction monitoring.
• Hands-on experience with very large datasets using data analytical tools e.g., ACL or SQL or Advanced Excel or Python is essential.