Director – Financial Intelligence & Algorithmic Risk Governance

Job Overview

Director – Financial Intelligence & Algorithmic Risk Governance

Jurisdiction: United Arab Emirates

Position Overview

This role is issued as an Executive Terms of Reference (ToR), establishing accountability for financial intelligence, algorithmic risk governance, and automated decision architecture in fintech ecosystems.

The position ensures that financial systems reason reliably, transparently, and ethically, balancing innovation with regulatory compliance and operational resilience.

Mandate Scope

• Design and govern financial intelligence systems for transaction monitoring, credit risk, fraud detection, and portfolio oversight.

• Establish governance frameworks to ensure explainability, auditability, and compliance with international regulations.

• Integrate macroeconomic, transactional, and behavioral datasets into adaptive, algorithmic decision models.

• Develop frameworks for bias detection, mitigation, and system performance monitoring.

• Provide executive guidance on AI/ML adoption in financial systems while maintaining ethical and regulatory alignment.

Core Responsibilities

• Architect end-to-end pipelines for financial intelligence, ensuring resilience and traceability.

• Define lifecycle governance and validation for algorithmic models.

• Translate complex analytics into executive-level and regulatory reporting.

• Produce thought-leadership and strategic intelligence briefs on AI, predictive analytics, and fintech systemic risk.

• Lead cross-functional teams in architecture, analytics, and compliance integration.

Professional Requirements

• 12+ years in financial risk management, AI-driven analytics, or fintech intelligence systems.

• Strategic, not purely technical, understanding of algorithmic decision-making in finance.

• Exceptional communication skills for executive and regulatory audiences.

• Strong ethical grounding and prior experience in governance or regulatory oversight of financial systems.

Operational Model

• Fully remote, research-driven, milestone-based engagement.

• Performance measured on analytical rigor, governance quality, and decision reliability.

• Executive-level autonomy, with accountability across organizational and regulatory boundaries.

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