As a Quant Modelling Analyst you will be a member of the Model Risk Governance and Review group in Bengaluru covering Counterparty Credit Risk models where you will have exposure to multiple assets classes, collateral modelling, advanced modelling methodologies as wells as day-to-day interaction with Quantitative Research teams, Risk functions and trading desks. Your position will focus on the following activities:As part of the firm’s model risk management function, the Model Risk Governance and Review group, you would be charged with developing model risk policy and control procedures, performing model validation activities, providing guidance on a model’s appropriate usage in the business context, evaluating ongoing model performance testing, and ensuring that model users are aware of the model strengths and limitations. ou are passionate about quantitative finance and counterparty credit risk. Join a dynamic counterparty credit model risk team focusing on cutting-edge XVA and credit exposure model

Job responsibilities:

Perform Model validation of trading models/pricers used in XVA, Counterparty Credit Exposure and IMM/Capital calculations and regulatory stress testing.  Perform assessments of the conceptual soundness of model specification, the appropriateness of the methodology for its intended purpose, reasonableness of assumptions and reliability of inputs and assessment of model limitations Assess completeness of testing performed to support the correctness of the implementation Perform ongoing performance monitoring tests and regulatory/non-regulatory backtesting to ascertain that models are relevant and fit for purpose. Assist with model governance processes, model inventory and issue management and help to devise new model governance policies as and when required. Work closely with model developers, trading desks, and controls functions across the firm to understand methodology, usage and establish transparency around model controls, model limitations and performance

Required qualifications, capabilities, and skills:

Quantitative background with at least a bachelors degree in Mathematics, Science, Engineering, Statistics, Quant Finance, or similar. Strong quantitative, analytical, and problem-solving skills; knowledge of probability theory, statistics, mathematical finance, econometrics, numerical methods and stochastic calculus.  Strong communication and interpersonal skills; ability to multi-task and meet deadlines Ability to work independently, with remote supervision Risk and control mindset: ability to ask incisive questions, assess materiality and escalate issue

Preferred qualifications, capabilities, and skills

Knowledge and interest in Python programming Understanding of finance industry, particularly in modeling- valuation, risk, capital, forecasting, investment management