Quantitative Liquid Alternatives Portfolio Analyst

Goldman Sachs Group; New York (NY); On-site; USD 90,000 - 130,000; Full time

Job summary

Goldman Sachs Asset & Wealth Management is seeking an Analyst for the Quantitative Investment Strategies (QIS) group, focusing on Liquid Alternatives portfolio construction and active management in New York. You will drive daily rebalancing, risk attribution, and performance analysis for uncorrelated, factor-based strategies, combining economics, math, and advanced analytics.

The role requires strong programming, statistics, and data handling skills, with experience in derivatives being a plus.

Qualifications

• BA/BS in a quantitative field such as Statistics, Finance, Math, Computer Science, or Engineering preferred
• Excellent analytical and quantitative skills
• Creativity and ability to think outside the box
• Passion for systematic and quantitative investment
• Ability to work well in a fast-paced environment
• Solid understanding of statistics, linear algebra, and calculus
• Strong programming skills (Python, Matlab, R, C++, Java, or other languages)
• Exceptional attention to detail and strong operational discipline
• Knowledge of derivatives (futures, forwards, swaps, and options) and multi-asset strategies

Responsibilities

• Optimization and Rebalancing of Liquid Alternatives Portfolios
• Systematic Trade Generation and Execution Oversight
• Implementation and Testing of New Portfolios
• Collateral, Margin, and Cash Management
• Risk, Leverage, and Factor Exposure Monitoring
• Investment Process Innovation & AI Automation

Skills

Python

Matlab

R

C++

Java

Statistics

Derivatives knowledge

Quantitative investing

Analytical skills

Attention to detail

Education

BA/BS Degree in a quantitative field

Job description

Goldman Sachs Asset & Wealth Management is seeking an Analyst for the Quantitative Investment Strategies (QIS) group, focusing on Liquid Alternatives portfolio construction and active management in New York. You will drive daily rebalancing, risk attribution, and performance analysis for uncorrelated, factor-based strategies, combining economics, math, and advanced analytics.

The role requires strong programming, statistics, and data handling skills, with experience in derivatives being a plus.