Quant jobs / Goldman Sachs

Senior Quantitative Engineer – Marquee Portfolio Analytics

A leadership engineering role on Marquee, the firm's digital platform for institutional clients, owning portfolio analytics such as risk models, attribution and optimisation. You lead a global engineering team.

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 factor risk, attribution and portfolio optimisation features on the platform
Design scalable data models and real-time calculation environments
Manage and mentor engineers across time zones
Turn client feedback and product plans into production features
Keep systems reliable through CI/CD and testing

What they ask for

Required

Factor risk modelling
Performance and risk attribution
Portfolio optimisation
Python and Java
Large financial datasets
Team management
Presenting to institutional clients

Preferred

AWS and distributed computing
API design

Education: Master's or PhD in financial engineering, computer science, maths, physics, statistics or similar
Experience: 5+ years in quantitative research, quant engineering or financial modelling at VP level
Languages and tools: Python
Java
Markets: equities

How to prepare

Build a factor risk model and performance attribution engine in Python
Implement constrained portfolio optimisation and test its sensitivity
Study equity factor models like Barra-style structures
Design a small API serving portfolio analytics with tests and CI

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.