Quant jobs / Goldman Sachs

Liquidity Metrics Quant – Vice President

A risk-modelling and engineering role in the firm's Core Engineering group, measuring liquidity risk with quantitative models. It is code-heavy and supports Risk, Treasury and Finance functions.

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.

Develop and update liquidity and risk models using statistics, optimisation and machine learning
Analyse trends and drivers behind changes in risk measures
Maintain large-scale risk systems in code
Present model results and insights to technical and business audiences
Adapt models as the business and risk environment change

What they ask for

Required

Strong programming in C, C++, Java or Python
Data structures and algorithms
Statistics and applied maths
Scalable system design
Risk modelling
Communication skills

Preferred

Financial markets and risk management familiarity

Education: Bachelor's or postgraduate degree in maths, physics, electrical engineering or a related technical discipline
Experience: 6+ years in software development
Languages and tools: C++
Java
Python
Scala

How to prepare

Build a liquidity-risk calculation, such as a stressed cash-outflow model, with clean tested code
Study liquidity regulation basics (LCR, NSFR) and funding concepts
Practise designing a scalable risk calculation service
Refresh regression and optimisation methods used in risk models

What to study

The Risk 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.