Goldman Sachs · 4 days ago

Quantitative Engineering, Associate - Risk Engineering

Dallas, TX

Full-time

Onsite

Mid Level

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Responsibilities

Partnering with business units and broader Credit department to assess data availability, data sufficiency, and appropriate modelling approaches.

Designing and writing data queries to extract credit data from credit systems and conducting analysis of portfolio profiles/performance, deep dive analysis of trends, and summarizing findings.

Developing and monitoring the risk models and/or segmentation specific to the retail/securitization exposures.

Quantification of the Basel risk and Stress-loss parameters utilizing the models/segmentation.

Implementing coding infrastructure and environment to facilitate analysis related to development and testing of models/scenarios.

Documenting the model development/quantification procedures.

Performing the ongoing Model/Segmentation validation tests assessing the strength/stability/accuracy of the models.

Establishing requirements for data maintenance and management and working with Technology on implementation.

Qualification

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Quantitative AnalysisPythonJavaC++Project ManagementProblem-SolvingCommunicationOrganizationalConsumer Risk ModelsRisk Segmentation SystemsSecuritizations

Required

Strong quantitative and analytical skills with advanced degree (Masters preferred) in a quantitative discipline (Econometrics, Statistics, Mathematics, Financial Engineering etc.)

Ability to quickly learn and utilize quantitative modeling techniques

Strong coding skills preferably with a working knowledge of Python, Java or C++

Excellent written and verbal communication skills

Strong project management and organizational skills and the ability to manage multiple assignments concurrently