Job Duties: Associate, Software Engineering with Goldman Sachs & Co. LLCin Salt Lake City, Utah. Provide data-driven insights and effective technologies for firmwide risk management. Identify, design, and implement the best means of delivering risk information through compelling narratives, tools and visualizations to increase understanding and awareness of risk. Assist with innovating and designing new analytics and visuals, leveraging internal and external programming languages and software. Analyze, visualize, and oversee sets of data used in risk management and control functions. Provide a quantitative application to storytelling, leveraging risk engineering processes to maximize significance, quality, efficiency, speed, and reliability while ensuring clear accountability and attribution. Perform anomaly detections in large data sets, investigating the cause and recommending corrective actions. Work in close collaboration with bankers, traders, and portfolio managers as well as risk modelers and technology across the firm.
Job Requirements: Master’s degree (U.S. or foreign equivalent) in Mathematics, Finance, Electronics & Communications Engineering, Computer Science, Statistics, Business Analytics, or a related field and one (1) year of experience in the job offered or in a related field OR Bachelor’s degree (U.S. or foreign equivalent) in Mathematics, Finance, Electronics & Communications Engineering, Computer Science, Statistics, Business Analytics, or a related field and three (3) years of experience in the job offered or in a related field. Prior employment must include one (1) year (with Master’s degree) or three (3) years (with Bachelor’s degree) with: working with users to understand business requirements to design and develop low-cost and adoptive technical solutions; risk management at a large financial institution or a consulting organization, including experience in liquidity, regulatory, or credit risk; querying and aggregating data from a database, performing trend analysis, and visualizing results within a dashboard for the analysis of financial models used in credit risk management; examining risk factors impacting credit exposure; analyzing and explaining market trends to senior risk managers and financial regulators; and working with data management, including data flows, data mining, or data modeling.
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