Job Overview
Remote Executive Director of Multiscale Stochastic Finance & Systemic Risk – United Arab Emirates
Location: Remote – UAE (GCC)
Employment Type: Full-Time, Remote
Compensation: Exceptional Base + Performance-Linked Incentives + Equity
Overview:
The UAE seeks a visionary Executive Director of Multiscale Stochastic Finance & Systemic Risk to architect mathematically provable digital finance infrastructures spanning tokenized assets, decentralized settlement protocols, and AI-driven liquidity governance. The role demands the synthesis of measure-theoretic probability, stochastic PDEs, homotopy type theory, category-theoretic financial modeling, and AI-assisted systemic risk orchestration.
Key Responsibilities:
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Construct multi-agent stochastic partial differential equations to model liquidity dynamics, derivative pricing, and systemic risk across high-dimensional market manifolds.
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Formalize category-theoretic functors representing relationships between financial instruments, smart contract protocols, and cross-border payment networks.
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Apply homotopy type theory to verify compositional invariants of distributed ledgers and smart contract architectures.
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Develop tensor network models and topological data frameworks for counterparty risk, contagion analysis, and network resilience evaluation.
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Lead a transdisciplinary team of cryptoeconomists, quantitative engineers, and AI researchers, establishing simulation validation, proof-of-concept pipelines, and continuous systemic risk assessment.
Required Expertise:
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PhD or equivalent in Mathematical Finance, Computational Physics, Applied Category Theory, or Formal Methods.
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Mastery of Ito/Stratonovich calculus, Lévy processes, nonlinear PDEs, stochastic control, and high-dimensional Monte Carlo methods.
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Deep experience in blockchain consensus design, smart contract verification, and distributed computation.
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Proficiency in Python, Julia, Haskell, Rust, C++, and associated quantitative or blockchain libraries.
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Comprehensive knowledge of UAE Central Bank regulations, cross-border settlements, AML/CFT protocols, and ISO 20022 standards.
Preferred Attributes:
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Publications in stochastic network theory, algorithmic finance, or formal verification of financial protocols.
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Demonstrated experience in multi-agent reinforcement learning for systemic risk and liquidity optimization.
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Ability to operationalize abstract mathematical constructs into deployable fintech systems.
Impact:
Redefine UAE’s digital finance ontology, constructing mathematically coherent, AI-mediated infrastructures that integrate systemic risk management, liquidity orchestration, and decentralized asset governance.
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