Join our dynamic team as a Market Risk Quant focused on model validation and development. This role is crucial for evaluating and enhancing our market risk (including FRTB IMA/SA and Basel 2.5), counterparty credit risk, and pricing models. You will leverage your expertise in statistical modeling, quantitative research, and market risk management to ensure the robustness and accuracy of our financial models.

We are looking for candidates with a strong quantitative background and practical experience in developing and validating complex financial models. Your insights will directly contribute to mitigating risk and driving strategic decisions within our Regulatory & Financial Risk practice.

Conduct thorough independent reviews and validations of Market Risk Models, encompassing FRTB (IMA & SA), Basel 2.5, VaR, Expected Shortfall, and Sensitivities.

Validate Counterparty Credit Risk Models, including IMM/internal exposure models (EPE, EE, PFE), XVA models, and Margin models (DIM, SIMM).

Perform comprehensive assessments of Stress Testing Models such as CCAR, DFAST, and ICAAP.

Evaluate model inputs, assumptions, and outputs, ensuring conceptual soundness and methodological appropriateness.

Conduct performance testing, benchmarking, sensitivity analysis, and back-testing to assess model efficacy.

Review model implementations, identify potential risks, and recommend remediation actions.

Prepare detailed validation and model risk reports that align with regulatory standards (e.g., SR 11-7, ECB, PRA).

A Master's degree in a quantitative discipline such as Quantitative Finance, Financial Mathematics, Statistics, Economics, Engineering, or an MBA is required.

Possess 5-8 years of relevant professional experience.

Demonstrate sound knowledge and approximately 2-7 years of experience in at least one of the following areas: Market Risk models (VaR/RNIV, IRC, SA-CVA, FRTB SA/IMA), Stress Testing and Capital models (CCAR, DFAST, ICAAP), or CCR (SACCR, XVA, risk factor simulation, margin models like IM/VM/SIMM, exposure models).

Exhibit a strong understanding of Market Risk metrics (VaR, Expected Shortfall, sensitivities, FRTB, back-testing) and CCR metrics (EPE, EE, PFE, EAD, SA-CCR, margin models).

Proficiency in stochastic calculus, probability theory, change of measure, numerical methods, statistical techniques (e.g., ADF, KPSS, Durbin-Watson), stress testing, scenario analysis, and risk management strategies is essential.

Familiarity with derivatives and financial instruments across equities, fixed income, FX, and commodities is necessary.