Quant jobs / Goldman Sachs

AI Model Validation – Associate

A role in the firm's model risk group validating AI and machine-learning models. You work with AI researchers and developers to understand methods and test them independently.

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.

Test AI models for accuracy, explainability and robustness
Build benchmark models for comparison
Document risks and limitations found in testing
Work with developers to resolve issues

What they ask for

Required

Python with NumPy, Pandas and a deep learning library
Statistical modelling
Machine learning algorithms
Analytical problem solving
Clear communication

Preferred

Degree in computer science, maths, physics or engineering

Education: Bachelor's, Master's or PhD in a quantitative field preferred
Experience: Associate level; no specific years stated
Languages and tools: Python
TensorFlow
PyTorch
NumPy
Pandas

How to prepare

Train a classifier and probe it for overfitting, leakage and feature instability
Learn explainability techniques and where they break down
Write a benchmark model and compare it fairly with a more complex model
Practise a short validation memo covering scope, tests and findings

What to study

The Model Validation 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.