Internal Audit- Dallas - Vice President, Data Analytics - 7718233

Job Duties: Vice President, Data Analytics with Goldman Sachs & Co. LLC in Dallas, Texas. Lead a global team of data scientists and data analysts to create and execute data analytics strategy within the context of audit responsibilities, such as risk assessment, audit planning, creation of reusable tools and providing innovative solutions to complex problems. Develop strategic solutions to aggregate, analyze, and visualize data. Build production-ready analytics tools to automate repeatable and reusable processes following industry-wide software development lifecycle standards within internal divisions. Work with audit teams and fellow engineers to design self-service data products that enable auditors to work with firm data and more efficiently and effectively identify potential risk. Partner with audit teams to help identify risks associated with businesses, facilitate strategic data sourcing, and develop innovative solutions to increase efficiency and effectiveness of audit testing. Help internal divisions understand the tools, approaches, and infrastructure available to them. Assess various firmwide datasets for data quality to understand potential of data sources, limitations, or issues for audit.

Job Requirements: Bachelor’s degree (U.S. or foreign equivalent) in Computer Science, Computer Engineering, Information Systems, or a related field, and five (5) years of experience in the job offered or in a related role. Prior employment must include four (4) years of experience with: building end-to-end web services and APIs using Python on a framework including Flask, Djang, or FastAPI to automate recurring analytics use-cases and machine Learning algorithms and exposure to supervised and unsupervised learning, such as linear, and logistic regression, SVM, Random Forest and Boosting, and Clustering and Patterns Recognition techniques. Prior employment must include two (2) years of experience with: relational Database Management Systems (RDBMS) and Datawarehouse concepts and using SQL to extract, transform, and analyze data coming from diverse types of databases; natural Language Processing (NLP) analytics using Python-based NLP libraries and performing text extraction using Python; building, reviewing, and deploying notebooks and APIs using Python and SDLC (Software Development Lifecycle) tools; and development and site administration with visualization tools, Tableau or PowerBI, to build, deploy, maintain, and enforce the SDLC, and secure SDLC for visualization tools built using Tableau, PowerBI, or similar visualization tools.

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