Quant jobs / Goldman Sachs

Quantitative Strategist – Prime Brokerage Client Analytics

A client-facing quant role in the Prime Brokerage business, building analytics platforms and running analysis on hedge fund trends and portfolios. You also research factor and macro models.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Build analytics that track market and hedge fund trends
Run deep-dive analyses of client portfolios
Research or implement equity and FICC factor and macro models
Present findings to clients as a subject matter expert
Use AI tools to speed up research and workflows

What they ask for

Required

Programming in Java or Python
Quantitative or analytical professional experience
Client communication
Handling large datasets
Initiative on several projects

Preferred

Portfolio construction, risk models and factor analytics
Equity or FICC familiarity
Probability and machine learning
High-pressure delivery

Education: BS, MS or PhD in applied maths, data science, engineering, physics or finance
Experience: 2+ years in a quantitative, analytical or fintech role
Languages and tools: Java
Python
Markets: equities, fixed-income

How to prepare

Build a factor model and decompose a hedge fund-style portfolio's exposures
Study hedge fund positioning and flow data, such as 13F filings
Practise presenting a quantitative finding to a non-specialist in one page
Learn how prime brokerage financing and clients work

What to study

The Portfolio and Factor Quant roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

Read the full posting on Goldman Sachs’s site before applying: requirements, location and pay can change after we check them.

View the posting on Goldman Sachs’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Goldman Sachs and doesn’t handle applications.