AI-Driven Risk & Fraud Quant

Goldman Sachs; New York, Northern (NY, KY); Hybrid; USD 115,000 - 180,000; Full time

Job summary

Goldman Sachs in New York seeks a Quantitative Strategist on the PWM Risk Strats team to build models that streamline risk management, detect fraud at scale, and enable data-driven decisions across Wealth Management. You will develop and deploy ML models, deliver risk metrics for financial and non-financial risks, and collaborate with risk, fraud, and portfolio teams to address clients’ investment goals.

A strong background in mathematics, programming (Python, Spark), and time-series analysis is

Qualifications

• Bachelor, Masters or Ph.D. in a quantitative or engineering field.
• 1–3 years of experience in quantitative modeling and software development.
• Programming and mathematical skills are required.
• Creativity, problem-solving skills, and ability to communicate complex ideas to diverse audiences.
• A self-starter, should be able to work independently as well as in a team.
• Excellent understanding of ML techniques and algorithms; gradient boosting, random forests a plus.
• Experience with Python (Pandas, NumPy, Scikit-learn) and Spark.
• Experience with prompt engineering, working with LLM models, and MCP.
• Background in statistics, including time-series and regression analysis; SQL and OO programming.

Responsibilities

• Develop ML models for fraud and anomaly detection and workflow enhancements.
• Deliver risk metrics and analytics for financial and non-financial risks across wealth management.
• Develop AI-led solutions to improve efficiency and accuracy in risk management.
• Build and maintain robust risk management tools and reporting.
• Collaborate on design of strategies to meet clients’ investment goals.
• Develop and maintain risk analytics tools across multiple asset classes.
• Build and maintain infrastructure of Strategists’ analytical systems.

Skills

Programming & math skills

Creativity

Problem solving

Communication

Self-starter

Machine learning

Prompt engineering

LLM models

MCP

Time-series analysis

Regression analysis

OO programming

SQL

Education

Bachelor, Masters or Ph.D. in a quantitative or engineering field

Tools

Python

Pandas

NumPy

Scikit-learn

Spark

Job description

Goldman Sachs in New York seeks a Quantitative Strategist on the PWM Risk Strats team to build models that streamline risk management, detect fraud at scale, and enable data-driven decisions across Wealth Management. You will develop and deploy ML models, deliver risk metrics for financial and non-financial risks, and collaborate with risk, fraud, and portfolio teams to address clients’ investment goals.

A strong background in mathematics, programming (Python, Spark), and time-series analysis is