• Vice President, RSK3855350

    Location(s) US-UT-Salt Lake City
    Job ID
    Schedule Type
    Full Time
    Vice President/Executive Director
    Risk Management
    Business Unit
    Enterprise Risk Management
    Employment Type

    Vice President with Goldman Sachs & Co. LLC in Salt Lake City, UT.


    Work Schedule: 40 hours per week (9:00 a.m. to 6:00 p.m.)



    Duties: Vice President with Goldman Sachs & Co. LLC in Salt Lake City, UT. Develop and monitor risk models and/or segmentation specific to the retail/securitization exposures. Develop, implement, and monitor credit risk models to quantify capital parameters, such as probability of default (PD), loss given default (LGD), and exposure at default (EAD), complying with Basel III regulatory requirements. These models are used in estimating the Credit risk weighted assets for several of the Retail consumer financial products that include mortgages (first lien, home equity loans), personal loans, student loans, credit cards, small balance commercial real estate and small-medium enterprise loans. Participate in the governance of risk models, including working with Model Risk Management, Businesses, Technology and Department Management. Provide comprehensive technical documentations of the models covering model purpose, model specification, testing description, and empirical evidences. Document the model development/quantification procedures. Maintain and support model performances: calibration of models, examine test performances, update historical time series as market evolves, and adapt the changes in market dynamics to ensure appropriate model outcome. Address model limitations/uncertainties revealed from independent model review process to further enhance the models and perform quantitative analysis on questions raised by regulators. Quantify regulatory (e.g. Basel) risk parameters utilizing the models/segmentation. To comply with Basel Rules, Retail capital parameters need to be quantified by grouping the customers in to homogenous risk groups/segments. Advanced statistical/quantification techniques such as logistic regression modeling, linear regression modeling, decision trees, clustering, CHAID algorithmic techniques, differentiation testing techniques such as Z-test/Bonferroni tests etc. are utilized in achieving the homogeneous segmentation. Perform on-going Model/Segmentation validation tests assessing the strength/stability/accuracy of the models. Along with the statistical techniques, computer modeling and machine learning approaches are utilized to perform prediction and pattern recognition in the data attributes to support the financial data-driven decision making towards the use of these attributes in the statistical models/segmentation. Establish requirements for data maintenance and management and work with Technology on implementation. Implementation of the models in production using sophisticated software is part of the job: developing a comprehensive software code to execute the model in production environment, design tests to ensure the accuracy of implementation, as well as test for the continuous functioning of the models. Partner with business units and broader Credit department to assess data availability, data sufficiency and appropriate modeling approaches.


    Job Requirements: Master’s degree (US or foreign equivalent) in Statistics, Mathematics, Financial Mathematics, or Financial Engineering. Three (3) years of experience in the job offered or a related role. Must have three (3) years of experience with: applying knowledge of building Statistical models (including Linear Regression, Logistic Regression, Generalized Linear Models, and Time-Series Models) to develop capital parameters, that include probability of default (PD), loss given default (LGD), and exposure at default (EAD); applying knowledge of segmentation approaches (including clustering, CHAID, and decision trees  approaches) to achieve the homogeneous segmentation for Retail consumer financial products such as mortgages (first lien, home equity loans), personal loans, student loans, credit cards, small balance commercial real estate or small-medium enterprise loans;  applying knowledge of Data query tools, such as SQL, SAS, R, Python, Spark or Hadoop programming to clean and analyze data and develop/execute capital models; documenting models/approaches clearly detailing the technical approaches utilized; and applying the understanding of Regulatory requirements/expectations in quantifying the Capital parameters including PD, LGD and EAD.


    The Goldman Sachs Group, Inc. is a leading global investment banking, securities and investment management firm that provides a wide range of financial services to a substantial and diversified client base that includes corporations, financial institutions, governments and individuals. Founded in 1869, the firm is headquartered in New York and maintains offices in all major financial centers around the world.

    © The Goldman Sachs Group, Inc., 2019. All rights reserved Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Vet.