Background
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The Market Risk Strats team within Risk Engineering is a quantitative modelling team focusing on market risk and capital models. The team is primarily responsible for designing, implementing and maintaining quantitative models for metrics such as Value-at-Risk, Stress Tests and Capital. Risk Engineering is a multidisciplinary group of quantitative experts who are tasked with modeling, producing, reviewing, interpreting, explaining and communicating risk & capital metrics and analytics used to ensure the firm adheres to its Risk Appetite and maintains the appropriate amount of Risk Capital. Risk Engineering provides risk & capital metrics, analytics and insights to the Chief Risk Officer, senior management, regulators, and other firm stakeholder |
Role Responsibilities
The responsibilities can include:
- Developing, refining and maintaining robust and production quality market risk models (such as value-at-risk, stress tests) and capital models. This involves identifying market risk factors for various products and building mathematical models to capture their economic and statistical characteristics.
- Implementing, testing and productionizing models and analytics. This involves prototyping models, implementing them and designing tests to ensure the quality of implementation as well as tests for the continuous functioning of the models.
- Performing pricing analyses, risk and capital impact analyses.
- Building robust, systematic & efficient workflows, processes and procedures around the production of risk analytics for financial & non-financial risk, risk capital and regulatory reporting.
- Interact with various other groups such as risk managers, senior managers and stakeholders to explain the results of the models and analytics and provide quantitative advice.
Qualifications, Skills & Aptitude
Eligible candidates are preferred to have the following:
- Strong quantitative skills with a PhD degree in a quantitative discipline (Physics, Mathematics, Quantitative Finance, Computer Science, Engineering, etc.) or a Bachelor’s/Master’s degree in a quantitative discipline with 3-5 years of relevant work experience.
- Excellent command of mathematics, modeling and numerical techniques. Good knowledge of statistics, time series analysis, econometric modeling and probability theory.
- Strong programming skills and experience with a popular programming language (Java, C++, Python etc.).
- Hands-on experience of developing pricing models/risk models.
- Excellent written, verbal and team-oriented communication skills.