Regulatory Quant & Intelligence Specialist (Regulatory Compliance)

Role Overview

We are seeking a mid-level Regulatory Quant & Intelligence Specialist to sit within the Regulatory Compliance function and build the organisation's AI-native legal and compliance intelligence capability. This role combines regulatory expertise, analytical/quant skills and AI-enabled workflow design to transform how regulatory and legal decisions are made, documented and automated across the business. You will model legal and regulatory reasoning into structured decision systems, design AI-enabled workflows for compliance operations, and ensure outputs remain explainable, auditable and aligned with the firm's risk appetite and regulatory obligations.

Key Responsibilities

Regulatory Decision Modelling

Translate legislation, regulatory guidance and internal policies into structured decision frameworks, rule sets and scoring models that can be embedded into compliance processes and tooling.

Define quantitative thresholds (risk scores, confidence levels, escalation triggers) that determine when automated decisions are appropriate versus when human review is required, aligned with regulatory expectations and internal governance.

AI-Enabled Compliance Workflows

Design and prototype AI-powered workflows for regulatory research, licensing analysis, policy drafting, onboarding/KYC, surveillance and incident management within the Regulatory Compliance function.

Collaborate with engineers and data teams to implement LLM/RAG/agentic workflows that support compliance advisory, regulatory mapping and ongoing monitoring, ensuring strong grounding, documentation and audit trails.

Quant Analysis and Evaluation

Build and maintain simple analytical/quantitative models to assess regulatory risk, scenario outcomes and potential enforcement impact, supporting proactive compliance strategy and licence/posture decisions.

Design evaluation frameworks to periodically test and calibrate decision models and AI-enabled workflows against real-world cases, internal incidents and regulatory feedback.

Regulatory Research and Intelligence

Conduct structured regulatory research across key jurisdictions (e.g. Singapore, EU/EEA, UK, Australia, Middle East) and maintain internal views on how evolving rules impact existing and new products.

Convert regulatory developments into machine-readable rules, guidance notes and internal playbooks that can be consumed by compliance staff and AI systems.

Governance, Documentation and Stakeholder Engagement

Draft and maintain documentation for decision frameworks, model assumptions, limitations and human-in-the-loop controls, aligned with AI governance and compliance best practices.

Partner with Legal, Product and Engineering to embed regulatory requirements into product design and internal tools, and support responses to regulators, auditors and internal risk committees where AI-enabled decisions are involved.

Requirements (Mid-Level under Compliance)

Quant mindset: technically fluent regulatory professional who thinks in systems - prompts, retrieval and evaluation - and redesign traditional compliance workflows from first principles into executable decision models used by both AI (LLMs, triage engines, agentic workflows, data pipelines) and humans.

Instinctively seeks the simplest, most automated way to deliver complex work without compromising quality or auditability.

3–5 years' experience in regulatory compliance, financial services law, or a related role within a financial institution, crypto/fintech firm, trading venue or regulator.

Strong understanding of financial services and VASP regulation, licensing frameworks, and cross-border regulatory issues (e.g. MAS, AUSTRAC, FCA, MiCAR, ADGM or similar regimes).

Demonstrated ability to independently build structured, tech-supported workflows or internal tools for legal/compliance processes (e.g. using Python, scripting, or no-/low-code platforms).

Experience working with or alongside LLMs, APIs, workflow orchestration or data/analytics platforms, with comfort iterating on prompts, retrieval strategies and evaluation metrics.

Strong analytical and computational thinking skills, able to formalise complex regulatory reasoning into clear models, diagrams and structured guidance for both humans and systems.

Excellent communication skills, with the ability to bridge Legal, Compliance, Engineering and Product, and to explain complex decision logic to non-technical stakeholders and senior management.

High degree of professional judgement, integrity and ownership, with comfort operating in fast-moving, ambiguous regulatory environments typical of crypto and fintech.

Profile / Behavioural Traits

Systems thinker with a builder's mindset, naturally inclined to redesign workflows from first principles rather than only optimise existing steps.

Technically curious and comfortable experimenting with AI tools and emerging technologies within a governed, compliant framework.

Pragmatic, commercially aware and able to balance regulatory risk, business objectives and operational constraints when designing decision models.