Quantitative Analyst – Risk Models & Analytics (VP)

SGX Group; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

A leading financial institution in Singapore is seeking a high-caliber quantitative professional to develop risk and pricing models. The ideal candidate will have an advanced degree and proven expertise in quantitative modelling, Python development, and derivatives risk analytics. This role emphasizes collaboration within a fast-paced environment to deliver impactful solutions. Competitive compensation and dynamic working conditions are offered.

Qualifications

• Proven expertise in quantitative modelling and derivatives risk analytics.
• Strong grasp of market microstructure and risk methodologies.
• Communicates clearly and influences stakeholders effectively.

Responsibilities

• Lead design of risk models across asset classes.
• Develop analytics for derivatives pricing and volatility.
• Work closely with risk users to identify improvements.

Skills

Quantitative modelling

Python development

Risk analytics

Critical thinking

Stakeholder engagement

Education

Advanced degree in quantitative discipline

Job description

Role Summary:

We are seeking a high-caliber quantitative professional to lead the development of SGX’s risk, margin, and pricing models, together with the analytics architecture that supports them. The role blends deep modelling expertise, strong market understanding, and hands‑on engineering, with meaningful influence on SGX’s multi‑asset risk framework and market structure.

Reporting to the Head of Risk Models and Analytics. The incumbent is expected to perform:

Key Responsibilities:

Model Development & Enhancement

• Lead the design and improvement of margin, stress, credit, liquidity, and exposure models across asset classes.
• Develop pricing, volatility, and risk‑sensitivity analytics for derivatives.

Analytics Engineering

• Convert model frameworks into robust, scalable Python code and oversee integration into production systems.
• Ensure enhancements are thoroughly tested, including UAT, and support smooth rollout into production.

Systems & Process Understanding

• Develop a deep understanding of SGX’s enterprise trading, clearing, settlement, and data‑lake systems — and how risk, processes, and workflows run across these platforms.
• Contribute to the design and requirements for risk processes, system enhancements, data flows, and platform upgrades across the clearing and trading value chain.
• Drive the evolution of SGX’s risk analytics platform in a fast‑moving, collaborative environment.

Stakeholder Engagement

• Work closely with risk users to explore needs, identify capability gaps, and shape improvements that close those gaps in an agile yet robust manner.
• Represent SGX’s risk methodology in discussions with policy teams, business units, market participants, regulators, and industry groups.

Governance & Validation

• Conduct scenario design, sensitivity studies, and model validation with clear governance and documentation.
• Identify opportunities to strengthen models, incorporate new market developments, and challenge established approaches where needed.

How We Work

• Operate within a flat, hands‑on team where everyone contributes directly to modelling, analytics, and system development.
• Collaborate closely with risk, technology, and business stakeholders to deliver impactful solutions.
• Embrace a fast‑paced, dynamic environment that values integrity, innovation, and continuous improvement.

Job Requirements

• Advanced degree in quantitative discipline (e.g., Mathematics, Statistics, Physics, Engineering, Computer Science).
• Proven expertise in quantitative modelling, Python development, and derivatives risk analytics.
• Experience in financial markets—ideally from exchanges, clearing, hedge funds, prop shops, fintech, or multi‑desk banking quant roles.
• Strong grasp of market microstructure, pricing, volatility, and risk methodologies, paired with modern engineering practices.
• Demonstrates curiosity, critical thinking, and the ability to connect models with real‑world market dynamics.
• Communicates clearly, influences stakeholders, and brings a builder’s mindset with ownership, initiative, and practical judgement.