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Senior Manager - Fraud Operations

Unlock employer Dubai, United Arab Emirates Posted: 14 Jan 2026

Financial

  • Estimate: $80k - $120k*
  • Zero income tax location

Accessibility

  • Apply from abroad
  • Visa Provided

Requirements

  • Experience: Senior
  • English: Professional

Position

As the Senior Manager - Fraud Operations, you will be part of the Regional Customer Experience team at the company. You will play a pivotal role leading the company’s fraud prevention strategy and oversee a team of Fraud Analysts focused on detecting, analysing, and mitigating fraudulent activities across our ecosystem. You’ll drive operational excellence, develop scalable fraud frameworks, and partner with Product, Data, and regional operations teams to strengthen platform integrity. This role combines leadership, analytics, and strategic problem-solving to ensure our fraud prevention evolves ahead of emerging risks.

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Location
Dubai, United Arab Emirates

Responsibilities

  • Own the end-to-end fraud operations strategy — from prevention and detection to response and continuous improvement.
  • Lead and mentor a team of Fraud Analysts, setting clear goals, guiding development, and ensuring delivery against fraud KPIs.
  • Define, track, and improve fraud-related KPIs, ensuring early detection and timely mitigation of risks.
  • Serve as the senior fraud representative with key stakeholders — Product, Finance, Legal, Marketing, and Operations.
  • Champion process automation and system enhancements that reduce manual intervention and improve fraud detection precision.

Requirements

  • Experience: 8+ years in fraud operations, risk management, or analytics in a high transaction-volume environment (e-commerce, fintech, payments).
  • Leadership: Proven experience leading and developing analytical or operations teams, ideally across multiple markets or regions.
  • Analytical Skills: Strong understanding of data analysis and fraud detection logic; proficiency in SQL or BigQuery preferred.
  • Education: Bachelor’s or Master’s degree in Economics, Statistics, Mathematics, Engineering, or related quantitative field.
  • Preferred: Familiarity with fraud detection tools, machine learning models, or rule-based systems; exposure to payments or chargeback management.
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