Asset & Wealth Management-Quantitative Engineering-New York-Associate

Asset & Wealth Management - Associate Quantitative Strategist in Wealth Management Strats

Our quantitative strategists are at the cutting edge of our business and solve real-world problems through a variety of analytical methods. As a member of our team, you will utilize your training in mathematics, programming, and logical thinking to build quantitative models that drive success in our business. Your problem-solving talents and aptitude for innovation will help define your contributions and enable you to find solutions to a broad range of problems, in a dynamic, fast-paced environment.

Responsibilities

As a strategist on our PWM Risk Strats team, you will work closely with various teams including risk management, fraud strategy and leadership. You will combine quantitative techniques and industry knowledge to build best in class models and tools that streamline risk management, detect fraud at scale, enable optimized data-driven business decision making, and optimize profitability.

Responsibilities include:

• Develop quantitative stress-based models and tools to manage firm's counterparty credit risk management in wealth management.
• Delivering valuation, risk metrics and quantitative analytics for financial and non-financial risks across wealth management.
• Develop AI-led solutions to improve efficiency and accuracy in risk management.
• Developing and deploying ML models for fraud and anomaly detection as well as business workflows enhancement
• Building and maintaining robust and systematic risk management tools and reporting
• Collaborating on the design of new and existing strategies to address clients' investment goals.
• Developing and maintaining risk management and portfolio analysis tools across multiple asset classes for senior management and portfolio managers.
• Building and maintaining infrastructure of Strategists' analytical systems.

About Goldman Sachs Wealth Management

Across Wealth Management, Goldman Sachs helps empower clients and customers around the world to reach their financial goals. Our advisor-led wealth management businesses provide financial planning, investment management, banking, and comprehensive advice to a wide range of clients, including ultra-high net worth and high net worth individuals, as well as family offices, foundations and endowments, and corporations and their employees. Our consumer business provides digital solutions for customers to better spend, borrow, invest, and save. Across Wealth Management, our growth is driven by a relentless focus on our people, our clients and customers, and leading-edge technology, data, and design.

Basic Qualifications

• Bachelor, Masters or Ph.D. in a quantitative or engineering field, e.g. mathematics, physics, quantitative finance, computational finance, computer science, engineering
• 1-3 years of experience in the job offered or related quantitative financial modeling and software development positions
• Programming and mathematical skills are required
• Creativity, problem-solving skills, and ability to communicate complex ideas to a variety of audiences
• A self-starter, should have ability to work independently as well as thrive in a team environment

Preferred Qualifications

• Experience with counterparty credit risk models and understanding of stress based risk models.
• Experience with prompt engineering, working with LLM models, and MCP.
• Previous work experience in: Utilizing statistical methods, including time-series and regression analysis; programming in object-oriented languages for efficient model implementations; manipulating data sets using relational databases and SQL.