Associate - 6985390 Jobs

Job Duties: Associate with Goldman Sachs & Co. LLC in Dallas, Texas. Quantitative engineering role responsible for developing, implementing, and documenting models for credit risk computations. This involves designing and implementing methodologies to identify risk factors and capture their financial and statistical characteristics. These models are used for various business-as-usual, risk, and regulatory stress testing processes. Design, implement, execute, and maintain a budgeting framework for the firm’s loan portfolios, that addresses expected risks in current macroeconomic environment. Develop models based on an understanding of derivatives pricing theory, financial markets and instruments, and statistical model building. Build and implement a model to predict probability of default (PD) and loss given default (LGD) of warehouse lending portfolios of varying underlying asset types, for model usage in Firm’s Comprehensive Capital Analysis and Review (CCAR) stress testing process, and Current Expected Credit Loss (CECL). Develop risk models and architectures to effectively identify, monitor, evaluate, and manage the firm’s risks, such as for the tail risk framework. Execute end-to-end development of models for new lending products. Create and maintain clear and complete technical documentation of the risk-model performance testing approach and process including the purpose, specification, description, and support for the choice of approach or model. Develop and maintain a complex computational framework that runs calculation of allowance for loan and lease losses (ALLL) under the CECL accounting framework. The result of this calculation is part of the Firm’s quarterly financial statements and external reporting. Communicate results (orally and in writing) to senior leaders. Collaborate with stakeholders across the firm to address data, model, and implementation issues.
Job Requirements: Master’s degree (U.S. or foreign equivalent) in Financial Mathematics, Applied Mathematics, Statistics, Economics, Mathematical Finance, Operations Research, or a related field AND one (1) year of experience in the job offered or in a related role. Must have one (1) year of experience with: executing time-series econometric modeling using techniques including linear regressions, error-correcting models, vector auto-regressions, principal components analysis, and state space models; performing quantitative and qualitative analysis using a broad range of economic and financial market data and analyzing the interdependencies between various asset classes and risk factors; performing statistical and quantitative analysis using a programming language or environment such as C++, Java, R, Stata, SAS, or Python; documenting processes and models along with creating presentations detailing analysis performed within the financial industry; working with regulatory requirements related to stress testing, risk identification and scenario design including CCAR or CECL; and performing analysis leveraging market risk, credit risk, liquidity risk and mathematical finance concepts.
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