Asset & Wealth Management-Quantitative… at Goldman Sachs · New York

Summary: Goldman Sachs is a leading global investment banking, securities and investment management firm. They are seeking an Associate Quantitative Strategist to utilize analytical methods to build quantitative models that drive success in wealth management, collaborating with various teams to enhance risk management and optimize business decision making. Responsibilities: - Developing and deploying ML models for fraud and anomaly detection as well as business workflows enhancement - Delivering 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 - 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 Required 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 - Excellent understanding of machine learning techniques and algorithms, such as gradient boosting decision trees, random forests, etc., is a plus - Experience with building models using common data science toolkits, i.e., Python (Pandas, NumPy, Scikit-learn) and Spark - 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 Required Skills: Quantitative modeling, Machine learning, Programming skills Important Skills: Statistical methods, Data science toolkits Benefits: Goldman Sachs is committed to providing our people with valuable and competitive benefits and wellness offerings, as it is a core part of providing a strong overall employee experience.