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.




Robust 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.
Strong 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 (Sydney)
🏢 Ethos BeathChapman
📍 Sydney