MRM- Credit Risk

Basic Information

Title : Associate / Senior Associate / Delivery Lead

Experience

: 2-6 Years

Location : Bangalore, Pune, Gurugram

Key Responsibilities

Gain deep understanding of the model inventory and the model risk management framework and lifecycle of the client

Validate CCAR Stress Testing for PPNR, balance sheet, scenario design and loss forecasting models used for internal risk management and provisioning as well as regulatory submissions

Assess the data requirements of the model, assumptions, and model methodology, analyze model outcomes, track ongoing model performance, and run stress tests on models based on company specific or regulatory stressed economic scenarios

Provide guidance to model owners for remediation of issues identified during validation to achieve MRM policy adherence

Provide support to client’s model risk management group in meeting their regulatory commitments

Interact proactively and build strong relationship with various model owners / stakeholders

Represent client’s model risk management group in interactions with model owners across lines of business

Drive adoption of best practices for model validation, assessment and documentation

Ability to work well in a team and feel comfortable presenting model validation findings

Gain ongoing knowledge of accepted practices and current research in the areas of mathematical modelling in finance and model risk management, though academic literature and respected financial / economic journals

Mentor junior quantitative analysts and conduct training sessions on mathematical modelling, quantitative analytics and risk management

Job Requirements

Qualification

M.Sc / PhD in Mathematics / Statistics / Economics or MBA Finance with experience in an MRM role (Tier I Colleges only )

Experience

Either, candidate should have exposure to CCAR modelling in an applied setting

Functional Competencies

Working knowledge in Stochastic Calculus, Linear Algebra, Differential Equations, Statistics, Simulation, Computational Methods and Numerical Analysis (working knowledge or coursework in mathematical finance will be an advantage)

Strong knowledge in mathematical techniques used in the development of VaR computation, Risk Charge calculations Tail Risk modelling

Working knowledge of Copula models, Monte Carlo simulation and techniques used in Traded Credit Risk modelling will be a huge plus

Well versed in regression modelling (Multiple Linear, Logistic, Polynomial, Beta, Poisson, and Time Series) as well as regularization techniques used in regression such as Ridge / Lasso / Elastic Net etc.

Working knowledge of machine learning models such as Decision Trees, Max Margin Classifiers and model ensemble ideas such as bagging, boosting and stacking

Well versed in one of R / Python and MS Excel

Research mindset, strong analytical and problem-solving skills

Strong documentation skills

Behavioral Competencies

Excellent team player

Good verbal and written communication skills

High accuracy and attention to detail

Strong conceptual thinking and ability to challenge traditional thought process

Ability to work efficiently in an unstructured environment

Self-motivated, ability to multi-task and work under high-pressure situations

Build strong relationships and networks across different business lines