Quantitative Strategist – Wealth Management (Associate)

Candidate Experience Site - Lateral; New York (NY); On-site; USD 115,000 - 180,000; Full time

Job summary

Goldman Sachs Wealth Management in New York, NY invites applications for an Asset & Wealth Management - Quantitative Strategist - Associate. You will build quantitative models, deploy ML solutions for fraud detection, and collaborate with risk management and portfolio teams.

The role requires a strong foundation in mathematics, programming (Python, Spark), and experience with data analysis, time-series methods, and OO languages.

Qualifications

• Bachelor, Masters or Ph.D. in a quantitative or engineering field (e.g., mathematics, physics, quantitative finance, CS).
• 1-3 years of experience in quantitative modeling and software development roles.
• Programming and mathematical skills required; experience with ML techniques and algorithms.
• Experience with Python (Pandas, NumPy, Scikit-learn) and Spark; familiarity with relational databases and SQL.

Responsibilities

• Develop ML models for fraud and anomaly detection and enhance business workflows.
• Deliver risk metrics and quantitative analytics for financial and non-financial risks.
• Build AI-led solutions to improve efficiency and accuracy in risk management.
• Create and maintain risk management and portfolio analysis tools across multiple asset classes.
• Collaborate on designing strategies to address clients’ investment goals.
• Maintain Strategists’ analytical systems infrastructure.

Skills

Python

Spark

Pandas

NumPy

Scikit-learn

Time-series

Machine Learning

SQL

OO programming

Education

Bachelor/Master/PhD in quantitative or engineering

Tools

Git

Jupyter

Job description

Goldman Sachs Wealth Management in New York, NY invites applications for an Asset & Wealth Management - Quantitative Strategist - Associate. You will build quantitative models, deploy ML solutions for fraud detection, and collaborate with risk management and portfolio teams.

The role requires a strong foundation in mathematics, programming (Python, Spark), and experience with data analysis, time-series methods, and OO languages.