Role Overview:

Our client is a leading global financial services organisation seeking a hands-on quantitative professional to join its Risk Analytics function. The role focuses on developing and enhancing market risk models supporting regulatory capital and internal risk management.

The successful candidate will work across VaR, RNIV, IRC and stress testing, covering asset classes including Rates, FX, Credit, Inflation and Equities. The role involves close collaboration with Risk, Front Office, Technology and Model Validation teams, with an opportunity to contribute to evolving market risk frameworks including FRTB.

Position Type: Permanent

Mode of Interview: Virtual

Experience: 2 - 6 Years in Model Development

Work Mode: Hybrid

Skills: Market Risk, Model Development, Quantitative Analytics, VaR, Python, Derivatives and Risk Modelling

Key Responsibilities:

Market Risk Model Development:

- Develop, maintain and enhance market risk models supporting VaR, RNIV, IRC and related capital metrics.

- Contribute to new model development across Rates, FX, Credit, Inflation and Equity products.

Model Testing & Analysis:

- Design and perform tests of model assumptions, methodologies and implementations.

- Investigate model issues, identify weaknesses and recommend improvements.

- Analyze complex datasets and model outputs to identify trends, anomalies and opportunities for enhancement.

Technology & Controls:

- Work with Technology teams to specify, implement and test system changes.

- Strengthen operational controls and improve the robustness of risk models.

Stakeholder Management & Reporting:

- Work closely with Market Risk, Credit Risk, Front Office, Technology and Model Validation teams.

- Prepare clear analysis and reporting for working groups and senior management.

- Contribute to wider Risk initiatives and ad-hoc quantitative projects.

Eligibility Requirements:

- Experience: 2 - 6 years in Model Development Market Risk within financial services.

- Strong understanding of financial markets and derivatives.

- Knowledge of derivatives pricing and quantitative modelling techniques.

- Strong analytical, data analysis and problem-solving skills.

- Proficiency in Python, R, Excel and VBA.

- Master's degree or higher in Mathematics, Statistics, Engineering, Computer Science, Quantitative Finance or a related quantitative discipline.

- Knowledge of VaR, IRC, RNIV and market risk stress testing preferred.

- Understanding of time-series analysis, probability theory, stochastic processes and stochastic calculus preferred.

- Exposure to C# or C++ is advantageous.

- Professional qualifications such as FRM, CQF or CFA would be an advantage.