Join a leading team focused on mitigating risk and uncovering opportunities within financial entities. This role involves critical work in model development and validation for Market Risk (FRTB IMA, SA and Basel 2.5), Counterparty Credit Risk, and Pricing models. You will leverage your expertise in statistical modelling, quantitative research, and market risk management to ensure model integrity and compliance.

This position offers a unique opportunity to contribute to a dynamic risk management environment, addressing everything from strategic risks to complex financial policies. The team's comprehensive risk services are designed to enhance board oversight and navigate the evolving landscape of financial threats.

Conduct independent reviews and validation of Market Risk Models (FRTB – IMA & SA, Basel 2.5, VaR, Expected Shortfall, Sensitivities) and Counterparty Credit Risk Models (including IMM/internal exposure models, XVA, and Margin models like DIM, SIMM).

Evaluate Stress Testing Models (CCAR, DFAST, ICAAP), assessing their inputs, outputs, and assumptions. Perform rigorous performance testing, benchmarking, sensitivity analysis, and back-testing to ensure model soundness.

Review model implementations to identify and document potential model risks, recommending appropriate remediation actions. Prepare comprehensive validation and model risk reports that align with regulatory expectations, such as SR 11-7, ECB, and PRA guidelines.

A Master’s degree in quantitative finance, Financial Mathematics, Statistics, Economics, Engineering, or an MBA is required, alongside 5-8 years of relevant professional experience. Strong knowledge and practical experience (2-7 years) in Market Risk models (VaR, RNIV, IRC, SA-CVA, FRTB) or Stress testing and Capital models (CCAR, DFAST, ICAAP) are essential.

Familiarity with Counterparty Credit Risk (CCR) concepts like SACCR, XVA models, risk factor simulation, margin models (IM, VM, SIMM), and exposure models is crucial. A solid understanding of Market Risk metrics (VaR, Expected Shortfall, sensitivities, FRTB, back-testing) and CCR metrics (EPE, EE, PFE, EAD, SA-CCR, margin models) is also expected.

Candidates must possess a strong grasp of stochastic calculus, probability theory, change of measure, numerical methods, and statistical techniques. Experience with stress testing, scenario analysis, risk management strategies, and familiarity with derivatives across various asset classes (equities, fixed income, FX, commodities) are highly valued. Certifications such as FRM, CFA, or CQF are considered a plus.