Quant jobs / Goldman Sachs

FICC Quantitative Researcher – Alpha Monetisation

A research role on a systematic FICC desk that trades against the bank's central risk book across rates, FX and commodities. The focus is turning predictive signals into realised profit.

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.

Improve how existing alpha signals are sized and combined into positions
Estimate dynamic covariance and decompose risk across rates, FX and commodity books
Test portfolio optimisation approaches against live trading results
Add features to the shared research infrastructure and signal analytics tools
Work with traders to move research ideas into the live book

What they ask for

Required

Quantitative research experience at a hedge fund, prop shop or systematic manager
Portfolio construction and optimisation
Risk modelling
Execution awareness
Python or Java
Strong quantitative academic record

Education: Excellent academic record in physics, maths, statistics, engineering or computer science
Experience: 2 to 10 years of buy-side quantitative research
Languages and tools: Python
Java
Markets: fixed-income, fx, commodities, multi-asset

How to prepare

Build a mean-variance and a risk-parity portfolio from a set of toy signals and compare turnover
Implement exponentially weighted and shrinkage covariance estimators
Study transaction-cost-aware position sizing
Read about the central risk book and how banks internalise flow

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.