Chief Architect of Digital Asset Governance & Quantitative Wealth Structuring

Job Overview

Chief Architect of Digital Asset Governance & Quantitative Wealth Structuring — Saudi Arabia

Location: Remote (Saudi Arabia Digital Transformation Ecosystem)

Region Focus: Saudi Arabia / GCC Institutional Wealth Infrastructure

Employment Type: Global Remote Executive

Discipline: Quantitative Wealth Engineering, Data-Driven Digital Asset Governance

Role Overview

As the Remote Chief Architect of Digital Asset Governance & Quantitative Wealth Structuring, you will lead the synthesis of governance frameworks, portfolio optimization systems, and decentralized asset control models based on mathematically formalized wealth structures.

This position requires constructing high-order models of institutional digital wealth — representing wealth as a multidimensional function $W=f(A,R,L,T)$, where $A$ denotes asset allocation tensors, $R$ represents risk curvature, $L$ denotes liquidity entropy, and $T$ time-based regulatory stability coefficients. The role blends financial ontology with advanced computational topology to define the next generation of wealth governance in the Saudi fintech ecosystem.

Key Responsibilities

• Quantitative Wealth Structuring:
  
  Develop and implement algorithmic portfolio optimization frameworks using mean-field games, stochastic dominance, and quantum-inspired Monte Carlo methods to model wealth distribution dynamics.

• Governance Systems Design:
  
  Create autonomous digital asset oversight mechanisms using blockchain formal verification, ensuring fiduciary accountability within mathematically validated governance models.

• Data-Driven Regulatory Compliance:
  
  Employ machine reasoning and ontological modeling to align digital asset behaviors with Saudi regulatory semantics and evolving digital transformation strategies.

• Computational Wealth Dynamics:
  
  Build high-dimensional simulation systems integrating tensor-based wealth evolution equations that reflect asset interactions, governance feedback loops, and capital efficiency gradients.

• Information Geometry of Wealth:
  
  Apply Riemannian geometric optimization to define wealth efficiency surfaces, identifying curvature points representing optimal asset rebalancing thresholds.

Candidate Profile

• Doctorate in Computational Finance, Mathematical Economics, or Theoretical Computer Science.

• 12+ years in fintech governance, algorithmic wealth management, or institutional asset engineering.

• Mastery of information theory, quantitative modeling, and blockchain-based compliance systems.

• Expertise in Python (NumPy, JAX), Haskell, or Scala for functional modeling of financial ontologies.

• Profound understanding of Saudi Arabia’s Vision 2030 fintech acceleration framework.

Strategic Relevance

This role positions you as an architect of digital financial ontology, encoding mathematical governance within institutional wealth infrastructures, and shaping how Saudi Arabia’s fintech sector internalizes the logic of decentralized, data-driven financial authority.

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