Job Overview
Remote Lead AI-Driven Payments Innovation Strategist – Qatar
Location: Remote (Qatar Alignment)
Employment Type: Senior Leadership Appointment
Compensation: Highly Competitive, Performance-Linked
Travel Requirements: Periodic engagements in Doha for strategic alignment briefings
Role Purpose
The Remote Lead AI-Driven Payments Innovation Strategist will design, model, and implement next-generation payment intelligence systems that advance Qatar’s positioning as an emerging fintech hub. The role centers on machine-learning-driven fraud analytics, omni-channel payment orchestration, digital wallet evolution, biometric authentication layers, and intelligent settlement pipelines.
Core Objectives
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Architect AI-powered fraud detection frameworks utilizing anomaly analysis, behavioral clustering, and predictive scoring.
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Design and optimize real-time payment routing engines leveraging decision trees, neural modeling, and adaptive heuristics.
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Integrate multi-currency wallet support and tokenized card rails aligned with regional compliance guidelines.
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Lead biometric-based authentication strategies including liveness detection, cryptographic signatures, and federated identity validation.
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Formulate system KPIs based on latency reduction, throughput efficiency, false-positive minimization, and fraud containment.
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Develop settlement algorithms optimized for reconciliation transparency and real-time regulatory reporting.
Technical Requirements
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8+ years of payment technology experience, with emphasis on ML/AI-enabled transaction intelligence.
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Deep knowledge of EMVCo standards, payment scheme switching, tokenization rails, and gateway infrastructures.
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Practical exposure to large-scale data engineering pipelines involving Spark, Kafka, and vectorized data flows.
Desirable Background
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Familiarity with the GCC payments regulatory framework and Qatar’s emerging digital economy initiatives.
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Experience with blockchain-anchored settlement sequencing and reconciliation intelligence.
Competencies
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Analytical rigor
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Regulatory sensitivity
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Innovation leadership
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Model interpretability
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