As a Senior Quantitative Risk Analyst, you'll combine quantitative analysis, data science and risk expertise to measure existing and emerging operational risks, develop analytical models and provide insights that support strategic decision-making.

Responsibilities

- Applying quantitative analysis and statistical modelling to assess operational risk and identify emerging trends.
- Managing and enhancing operational risk measurement models, including scenario quantification and stress testing.
- Analysing internal and external operational loss data to generate meaningful insights and support enterprise risk management.
- Managing operational loss data governance, including reconciliation, quality assurance and data integrity.
- Producing high-quality reporting, dashboards and visualisations that translate complex data into actionable business insights.

Essential

- 3+ years' experience in quantitative analysis, statistical modelling or advanced data analytics.




- Strong experience working with large, complex datasets, including data management, reconciliation and data quality controls.
- Advanced SQL skills and hands‑on experience using analytics and visualisation tools such as Power BI, Tableau and/or Alteryx.
- Solid quantitative modelling, statistical analysis and analytical problem-solving capability.
- Experience working within financial services.
- A degree in Mathematics, Statistics, Data Science, Actuarial Studies, Economics, Finance or another quantitative discipline.

Desirable

- Experience in operational risk, enterprise risk, capital management or quantitative risk measurement.
- Exposure to scenario analysis, stress testing or operational risk modelling.
- Knowledge of prudential regulatory frameworks and operational risk governance.

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📌 Senior Quantitative Risk Analyst (New South Wales)
🏢 Ethos BeathChapman
📍 New South Wales