Risk Engineering - Analytics And Reporting (salt Lake City,

Background Analytics And Reporting

Background Analytics and Reporting (AandR) is a group within Risk Engineering in the Risk Division of Goldman Sachs. The group ensures the firm's senior leadership, investors, and regulators have a complete view of the positional, market, and client activity drivers of the firm's risk profile allowing them to take actionable and timely risk management decisions. Risk Engineering is a multidisciplinary group of quantitative experts who are the authoritative producers of independent risk and capital metrics for the firm. Risk Engineering is responsible for modeling, producing, reviewing, interpreting, explaining, and communicating risk and capital metrics and analytics used to ensure the firm adheres to its Risk Appetite and maintains the appropriate amount of Risk Capital. Risk Engineering provides risk and capital metrics, analytics, and insights to the Chief Risk Officer, senior management, regulators, and other firm stakeholders.

Role Responsibilities

AandR delivers critical regulatory and risk metrics and analytics across risk domains (market, credit, liquidity, operational, capital) and firm activities via regular reporting, customized risk analysis, systematically generated risk reporting, and risk tools. AandR has a unique vantage point in the firm's risk data flows that, when coupled with a deep understanding of client and market activities, allows it to build scalable workflows, processes, and procedures to deliver actionable risk insights. The following are core responsibilities for AandR:

• Delivering regular and reliable risk metrics, analytics, and insights based on deep understanding of the firm's businesses and its client activities.
• Building robust, systematic, and efficient workflows, processes, and procedures around the production of risk analytics for financial and non-financial risk, risk capital, and regulatory reporting.
• Attesting to the quality, timeliness, and completeness of the underlying data used to produce these analytics.

Qualifications, Skills, and Aptitude Eligible candidates are preferred to have the following:

• Masters or Bachelors degree in a quantitative discipline such as data science, mathematics, physics, econometrics, computer science, or engineering.
• Entrepreneurial, analytically creative, self-motivated, and team-oriented.
• Excellent written, verbal, and team-oriented communication skills.
• Experience with programming in Python and SQL for extract transform load (ETL) operations and data analysis (including performance optimization).
• Experience in using languages such as R, Java, C++ is beneficial.
• Experience in developing data visualization and business intelligence solutions using tools such as, but not limited to, Tableau, Alteryx, PowerBI, and front-end technologies and languages.
• Working knowledge of the financial industry, markets, and products and associated non-financial risk.
• Working knowledge of mathematics including statistics, time series analysis, and numerical algorithms.
• 1-3 years of experience, preferably in financial, regulatory, or consulting environment.

The Goldman Sachs Group, Inc., 2018. All rights reserved Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Vet.