Quant jobs / Goldman Sachs

Quantitative Engineer – Asset Liability Management

A quant role in Corporate Treasury, building models for asset liability management, funding and net interest income forecasting. It sits within Core Engineering and works with senior Treasury stakeholders.

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 NIM, earnings-at-risk and funding cost projection models
Design stress and scenario frameworks across portfolios and legal entities
Model deposit behaviour, including betas and repricing lags
Run backtesting and monitoring to catch model drift
Support model validation and regulatory questions

What they ask for

Required

Quantitative finance experience in ALM or behavioural modelling
Python, C++ or Java
Fixed income and interest rate derivatives
Curve construction
Regression and time-series
Survival analysis
Explaining models to non-technical staff

Preferred

Using AI-based development tools

Education: Strong quantitative degree; Master's and PhD preferred
Experience: Proven quantitative finance experience in ALM or funding modelling
Languages and tools: Python
C++
Java
Markets: fixed-income

How to prepare

Build a deposit beta and repricing-lag model with regression on historic rate data
Construct a yield curve and compute earnings-at-risk under rate shocks
Study IRRBB and balance sheet management concepts
Backtest a behavioural model and design drift monitoring

What to study

The Treasury and ALM 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.