Risk Engineering – Analytics and Reporting; Salt Lake , UT | Salt Lake , UT

Risk Engineering – Analytics and Reporting (Salt Lake City, UT)

Job Description

Analytics & Reporting (A&R) 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 & capital metrics for the firm.

Risk Engineering is responsible for modeling, producing, reviewing, interpreting and explaining these metrics and analytics to ensure the firm adheres to its Risk Appetite and maintains the appropriate amount of Risk Capital. Risk Engineering provides risk & capital metrics, analytics and insights to the Chief Risk Officer, senior management, regulators, and other firm stakeholders.

• Deliver critical regulatory and risk metrics & 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.
• Build scalable workflows, processes and procedures to deliver actionable risk insights, leveraging deep understanding of client and market activities.
• Deliver regular and reliable risk metrics, analytics & insights based on deep understanding of the firm’s businesses and client activities.
• Build robust, systematic & efficient workflows, processes and procedures around the production of risk analytics for financial & non‑financial risk, risk capital and regulatory reporting.
• Attest to the quality, timeliness and completeness of the underlying data used to produce these analytics.

• 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 using languages such as R, Java, C is beneficial.
• Experience developing data visualization and business intelligence solutions using tools such as 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.