You are passionate about quantitative finance and counterparty credit risk. Join a dynamic counterparty credit model risk team that specializes in the review of advanced XVA and credit exposure models.

As part of the firm's model risk management function, the Model Risk Governance and Review group is responsible for developing model risk policy and control procedures, performing model validation activities, providing guidance on the appropriate use of models within business contexts, evaluating ongoing model performance testing, and ensuring that model users are aware of the model's strengths and limitations.

As a Quant Modelling Analyst/Associate in the Model Risk Governance and Review team, you will be covering Counterparty Credit Risk models. You will be exposed to multiple asset classes, collateral modelling, advanced modelling methodologies, and close interaction with Quantitative Research teams, Risk functions and trading desks.

• Model validation of trading models/pricers used in XVA, Counterparty Credit Exposure, IMM/Capital calculations, and regulatory stress testing.
• Perform assessment of the conceptual soundness of model specifications, the appropriateness of the methodologies for their intended purposes, the reasonableness of assumptions, the reliability of inputs, and assessment of model limitations.
• Evaluate completeness of testing performed to support the correctness of the implementation.
• Conduct ongoing performance monitoring tests and regulatory/non-regulatory backtesting to ensure that models remain relevant and fit for purpose.
• Assist with model governance processes, model inventory management, issue management and the development of model governance policies as needed.
• Work closely with model developers, trading desks, and controls functions across the firm to enhance understanding of methodologies, usage, and transparency around model controls, limitations, and performance.

• A quantitative background with at least a master's degree in Mathematics, Science, Engineering, Statistics, Quant Finance, or a related field.
• Strong quantitative, analytical, and problem-solving skills; knowledge of probability theory, statistics, mathematical finance, econometrics, numerical methods, and stochastic calculus.
• Relevant quantitative experience at a similar bank/asset management analytics setup.
• Strong communication and interpersonal skills with sound project management and organizational skills; ability to multi-task and meet deadlines.
• Ability to work independently, with remote supervision.
• A risk and control mindset with the capability to pose critical questions, assess materiality, and escalate issues as necessary.
• Proficiency and interest in Python programming.

• Domain expertise in XVA (CVA, DVA, FVA, KVA, etc.) and IMM.
• Experience in model validation and/or model development.
• Understanding of finance industry, particularly in modeling- valuation, risk, capital, forecasting, investment management