Risk, Quantitative Engineering, RES, Associate, Salt Lake City, UT

Goldman Sachs; Salt Lake City (UT); On-site; USD 70,000 - 110,000; Full time

Job summary

An established industry player is seeking a Risk, Quantitative Engineering Associate to join their dynamic team in Salt Lake City. This role involves developing statistical models for credit loss forecasting and collaborating across divisions to enhance risk management strategies. The ideal candidate will leverage their expertise in quantitative analysis and statistical techniques to provide valuable insights while fostering a culture of data-driven decision-making. If you are passionate about risk management and eager to contribute to innovative projects, this is an exciting opportunity to advance your career in a supportive and challenging environment.

Qualifications

• 3+ years of experience in quantitative analysis of credit products.
• Degree in a quantitative discipline; Master’s preferred.

Responsibilities

• Partner with business units to assess modeling approaches.
• Design and execute data queries, analyze portfolio performance.

Skills

Quantitative Analysis

Statistical Techniques

Data Analytics

Project Management

Communication Skills

Education

Bachelor's in Statistics

Master's in Engineering

Tools

SQL

SAS

R

Python

Tableau

Hadoop

Spark

Snowflake

Job description

Risk, Quantitative Engineering, RES, Associate, Salt Lake City, UT

Join to apply for the Risk, Quantitative Engineering, RES, Associate, Salt Lake City, UT role at Goldman Sachs

Risk, Quantitative Engineering, RES, Associate, Salt Lake City, UT

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Risk Engineering
Risk Engineering, part of the Risk Division, is central to Goldman Sachs' risk management framework. It provides metrics, data-driven insights, and technologies for risk management. The team is globally staffed with offices including Salt Lake City, Dallas, New Jersey, New York, London, Warsaw, Bengaluru, Singapore, and Tokyo. As a Risk Engineering team member, you will collaborate with various divisions and regional offices, engaging in diverse projects that ensure a challenging and dynamic work environment.

Job Description

Risk Engineering, a key part of the Risk Division, focuses on providing robust metrics, insights, and technologies for risk management across Goldman Sachs' global offices. The team interacts with multiple departments, enabling a multifaceted work environment.

Job Summary & Responsibilities

The Risk Economics Strats (RES) team is integral to risk management, responsible for developing macroeconomic and financial scenarios, creating statistical models for credit loss forecasting, risk management, and regulatory stress testing, and analyzing large datasets to extract insights about exposures. RES collaborates across divisions, offering a challenging, multifaceted environment. The team balances risk control with a commercial approach, emphasizing risk management, data analytics, and career development.

Responsibilities

• Partner with business units and Credit department to assess modeling approaches and data sufficiency.
• Design and execute data queries, analyze portfolio performance, identify trends, and recommend actions.
• Develop, document, and enhance risk models specific to credit exposures.
• Monitor models for stability, accuracy, and performance.
• Define data maintenance requirements and collaborate with Technology for implementation.
• Support portfolio credit risk loss forecasts and governance by tracking actual performance against expectations.
• Create portfolio performance reports using tools like Tableau.
• Prepare analytical reports and presentations for senior management, regulatory bodies, and committees.

Qualifications

• Minimum 3 years of experience in quantitative analysis of credit products, including model development and validation.
• Degree in a quantitative discipline (Statistics, Mathematics, Engineering, etc.); Master’s preferred.
• Experience with statistical techniques such as decision trees, regression, machine learning, and time series analysis.
• Proficiency with statistical tools like SQL, SAS, R, Python, and big data platforms like Hadoop, Spark, Snowflake.
• Knowledge of Basel A-IRB models, risk segmentation, stress testing (CCAR, DFAST), and portfolio loss forecasting is a plus.
• Strong communication, technical writing, and project management skills.

About Goldman Sachs

Goldman Sachs is committed to growth and community support, with a history dating back to 1869. Headquartered in New York, it has a global presence and is dedicated to diversity and inclusion, including providing accommodations for candidates with disabilities. Learn more at Goldman Sachs Disability Statement.

Seniority level

• Associate

Employment type

• Full-time

Job function

• Engineering and Information Technology

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