Quantitative Engineering, Risk Economics Strats, Vice President, Salt Lake

Quantitative Engineering, Risk Economics Strats, Vice President, Salt Lake City

Goldman Sachs

Risk Engineering, part of the Risk Division, plays a central role in Goldman Sachs’ risk management framework, providing robust metrics, data‑driven insights, and effective technologies. It is staffed globally with offices in Salt Lake City, Dallas, New Jersey, New York, London, Warsaw, Bengaluru, Singapore, and Tokyo. As a member, you will interface with various divisions across the firm and other regional offices, contributing to a challenging, varied, and multi‑dimensional work environment.

As a Vice President on the Risk Economics Strats (RES) team, you will be responsible for developing macroeconomic and financial scenarios, building statistical models for credit loss forecasting, and analyzing large risk‑metrics datasets to extract insights. Collaborating across multiple departments, you will balance risk management controls with commercial objectives, leveraging data analytics and fostering career development.

• Partner with business units and the broader Credit department to assess appropriate modelling approaches and evaluate data availability/sufficiency.
• Design and write data queries to extract data from credit systems and conduct analysis of portfolio performance, conduct deep dives into trends, summarize findings, and recommend changes.
• Build and enhance risk models specific to credit exposures and document the model development and quantification procedures.
• Continuously monitor models, assessing strength, stability, and accuracy.
• Establish requirements for data maintenance and management and collaborate with Technology to implement solutions.
• Support portfolio credit risk loss forecasting and governance by tracking actual performance against expectations.
• Create Management Loss Forecast reports using Tableau or similar visual interface tools to monitor portfolio performance at segment level (e.g., product, vintage, risk segment, score band, or marketing channel).
• Develop analytical reports and presentations for senior management, executive committees, and regulatory exams.

• 5+ years of quantitative analysis experience on credit products (loss forecasting, credit rating, pricing models, and/or market analytics), including model development and validation.
• Strong quantitative and analytical skills, with a degree in a quantitative discipline (Statistics, Mathematics, Applied Mathematics, Engineering, etc.); a master’s degree preferred.
• Proficiency in complex statistical techniques such as decision trees, regression modelling, machine learning, testing techniques, and time‑series analysis.
• Experience with statistical packages (SQL, SAS, R, Python, etc.) and tools for mining, manipulating, and aggregating large datasets on big‑data platforms (Hadoop, Spark, Snowflake, etc.).
• Background in Basel A‑IRB models, risk segmentation systems, regulatory stress‑testing processes (CCAR, DFAST), and/or portfolio loss forecasting preferred.
• Strong writing, presentation, and communication skills; technical writing and model documentation experience desired.
• Strong project management and organizational skills, with the ability to manage multiple assignments concurrently.

Goldman Sachs is a leading global investment banking, securities, and investment management firm, founded in 1869 and headquartered in New York. We are committed to finding reasonable accommodations for candidates with special needs or disabilities throughout our recruiting process. Learn more:

• Mid‑Senior level

• Full‑time

• Finance and Sales