Risk-NEW YORK-Vice President-Quantitative Engineering

Risk-NEW YORK-Vice President-Quantitative Engineering New York, NY

Job Description
The Risk Division aims to effectively identify, monitor, evaluate, and manage the firm’s financial and operational risks — including reputational risk — in support of the firm’s strategic plan.
Our client’s Risk division develops comprehensive processes to monitor, assess, and manage the risk of expected and unexpected events that may have an adverse impact on the firm. Risk teams play a critical function for the firm, driving how the firm takes and manages risk. Risk professionals execute critical day-to-day risk management activities, lead projects and contribute to the ongoing advancement of a robust risk management program. Effective coordination with executive management, business units, control departments and technology is critical for success.

RISK ENGINEERING
Risk Engineering, which is part of the Risk Division, is a central part of the risk management framework, with primary responsibility to provide robust metrics, data-driven insights, and effective technologies for risk management. Risk Engineering is staffed globally with offices including Dallas, New Jersey, New York, Salt Lake City, London, Warsaw, Bengaluru, Singapore, and Tokyo. As a member of Risk Engineering, you will interface with a variety of divisions around the firm as well as the other regional offices. The interaction with numerous departments and the diverse projects that ensue allow for a challenging, varied and multi-dimensional work environment.

Risk Engineering professionals are part of the value proposition of the firm and we balance our key functional responsibility of control with that of being commercial. RE has strong traditions of risk management, client service excellence and career development opportunities for our people.

Responsibilities
Develop and enhance risk models and measures to provide quantitative solutions and insights to both risk and regulatory capital management. The scope of the models covers broad risk stripes including Counterparty Credit Risk, Market Risk, Liquidity Risk, Operational Risk, Risk in Investing and Lending, and statistical evaluations of risk model performances. Examples of those highly quantitative models include Potential Exposures, Value at Risk, Modeled Liquidity Outflows, Stress testing and Scenario analysis, etc. The development of these models requires sophisticated and advanced mathematical and quantitative skills and is guided by financial theory, empirical evidences, and regulatory capital requirements.

Implement models and risk measures using sophisticated software. This involves developing a comprehensive software codebase including parallel computing to execute the model in a production environment and designing tests to ensure the accuracy of implementation as well as tests for the continuous functioning of the models.

Provide comprehensive documentation of the models covering the model purpose, model specification, testing description, empirical evidence, etc.

Maintain and support model performances. This involves on periodic recalibration of the models, examination of test outcomes, updating historical time series as the market evolves, and adapting to new market dynamics to ensure appropriate model outcomes.

Address model limitations/uncertainties provided by the independent model review process to further enhance the models.

Provide analysis of complex trades, risk estimation of the prospective trades by estimating the firm’s market, credit and liquidity risk, which serves as an important input for trade risk control and approval. Participate in regulatory stress testing requirements including Comprehensive Capital Analysis and Reviews (CCAR).

Qualifications
Post graduate degree /Bachelor’s degree (India) in Mathematics, Physics, Electrical Engineering or related technical discipline.
Experience in software development, including a clear understanding of data structures, algorithms, software design and core programming concepts.
Strong analytical and problem-solving skills using math, statistics, and programming.
Demonstrated ability to learn technologies and apply.
Excellent communication skills including experience speaking to technical and business audiences and working globally.
Strong programming experience in at least one compiled or scripting language (e.g. C, C++, Java, Python).
Experience in designing highly scalable, efficient systems.
Familiarity with financial markets and financial assets is a plus.