The Goldman Sachs Group
Quantitative Engineering, Risk Economics Strats, Vice President, Salt Lake City
The Goldman Sachs Group, Salt Lake City, Utah, United States, 84193
Overview
Risk Engineering
is part of the Risk Division and a central part of Goldman Sachs' risk management framework, with responsibility to provide robust metrics, data-driven insights, and effective technologies for risk management. Risk Engineering is staffed globally with offices including Salt Lake City, Dallas, New Jersey, New York, London, Warsaw, Bengaluru, Singapore, and Tokyo. As a member of Risk Engineering, you will interface with various divisions across the firm as well as the other regional offices, enabling a challenging, varied and multi-dimensional work environment. Job Summary & Responsibilities
The Risk Economics Strats (RES) team is a central part of the Goldman Sachs risk management framework with primary responsibility for: 1) developing macroeconomic and financial scenarios for firm-wide scenario-based risk management; 2) developing and implementing statistical models for credit loss forecasting, business-as-usual risk management and regulatory stress testing requirements; and 3) analyzing large datasets of risk metrics to extract valuable insights about the firm's exposures. RES professionals interface with a wide array of divisional, finance and risk management groups across the firm. The cross-disciplinary nature of RES projects creates a challenging and multifaceted work environment. RES balances risk management with commercial considerations, and offers opportunities for risk management, data analytics and career development. Responsibilities
Partner with business units and broader Credit department to assess appropriate modelling approaches as well as data availability and sufficiency. Design and write data queries to extract data from credit systems and conduct analysis of portfolio performance, deep-dive analysis of trends, summarize findings and recommend changes. Design, build, and enhance risk models specific to the credit exposures, and document the model development/quantification procedures. Perform ongoing model monitoring assessing the strength, stability and accuracy of the models. Establish requirements for data maintenance and management and work with Technology on implementation. Provide support for portfolio credit risk loss forecast and governance by tracking actual performance to expectations. Create Management Loss Forecast reporting using Tableau or other visualization tools to monitor portfolio performance at portfolio segment level (e.g., product, vintage, risk segment, score band, or marketing channel). Develop analytical reports and presentations for senior management, executive committees and regulatory exams. Qualifications
5+ years of experience in quantitative analysis of credit products (loss forecasting, credit rating, pricing models, and/or market analytics) including model development and validation. Strong quantitative and analytical skills with a degree in a quantitative discipline (Statistics, Mathematics, Applied Mathematics, Engineering, etc). Master’s degree preferred. Experience with complex statistical techniques such as decision trees, regression modeling, machine learning, testing techniques and time series data analysis. Experience with statistical packages like SQL, SAS, R, Python, and tools to mine, manipulate and aggregate complex consumer and transaction-level data on big data platforms such as Hadoop, Spark, Snowflake, etc. Background with Basel A-IRB models, risk segmentation systems, regulatory stress testing processes (CCAR, DFAST), and/or portfolio loss forecasting is preferred. Strong writing, presentation and communication skills; technical writing and model documentation experience desired. Strong project management and organizational skills with the ability to manage multiple assignments concurrently. About Goldman Sachs
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process.
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Risk Engineering
is part of the Risk Division and a central part of Goldman Sachs' risk management framework, with responsibility to provide robust metrics, data-driven insights, and effective technologies for risk management. Risk Engineering is staffed globally with offices including Salt Lake City, Dallas, New Jersey, New York, London, Warsaw, Bengaluru, Singapore, and Tokyo. As a member of Risk Engineering, you will interface with various divisions across the firm as well as the other regional offices, enabling a challenging, varied and multi-dimensional work environment. Job Summary & Responsibilities
The Risk Economics Strats (RES) team is a central part of the Goldman Sachs risk management framework with primary responsibility for: 1) developing macroeconomic and financial scenarios for firm-wide scenario-based risk management; 2) developing and implementing statistical models for credit loss forecasting, business-as-usual risk management and regulatory stress testing requirements; and 3) analyzing large datasets of risk metrics to extract valuable insights about the firm's exposures. RES professionals interface with a wide array of divisional, finance and risk management groups across the firm. The cross-disciplinary nature of RES projects creates a challenging and multifaceted work environment. RES balances risk management with commercial considerations, and offers opportunities for risk management, data analytics and career development. Responsibilities
Partner with business units and broader Credit department to assess appropriate modelling approaches as well as data availability and sufficiency. Design and write data queries to extract data from credit systems and conduct analysis of portfolio performance, deep-dive analysis of trends, summarize findings and recommend changes. Design, build, and enhance risk models specific to the credit exposures, and document the model development/quantification procedures. Perform ongoing model monitoring assessing the strength, stability and accuracy of the models. Establish requirements for data maintenance and management and work with Technology on implementation. Provide support for portfolio credit risk loss forecast and governance by tracking actual performance to expectations. Create Management Loss Forecast reporting using Tableau or other visualization tools to monitor portfolio performance at portfolio segment level (e.g., product, vintage, risk segment, score band, or marketing channel). Develop analytical reports and presentations for senior management, executive committees and regulatory exams. Qualifications
5+ years of experience in quantitative analysis of credit products (loss forecasting, credit rating, pricing models, and/or market analytics) including model development and validation. Strong quantitative and analytical skills with a degree in a quantitative discipline (Statistics, Mathematics, Applied Mathematics, Engineering, etc). Master’s degree preferred. Experience with complex statistical techniques such as decision trees, regression modeling, machine learning, testing techniques and time series data analysis. Experience with statistical packages like SQL, SAS, R, Python, and tools to mine, manipulate and aggregate complex consumer and transaction-level data on big data platforms such as Hadoop, Spark, Snowflake, etc. Background with Basel A-IRB models, risk segmentation systems, regulatory stress testing processes (CCAR, DFAST), and/or portfolio loss forecasting is preferred. Strong writing, presentation and communication skills; technical writing and model documentation experience desired. Strong project management and organizational skills with the ability to manage multiple assignments concurrently. About Goldman Sachs
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process.
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