Quant jobs / Goldman Sachs

AI Model Validation – VP

A senior role in the firm's independent model risk group, validating AI and machine-learning models. You work with AI developers and researchers to challenge methods and document risks.

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.

Lead independent validation of AI models for accuracy and robustness
Design validation methods and benchmark models for AI systems
Test model outputs and document limitations
Agree fixes with model developers and business owners

What they ask for

Required

Python with data science libraries
Statistical modelling
Machine learning algorithms
Quantitative model development or research experience
Strong communication

Preferred

PhD in a quantitative field
5+ years as a model developer or data researcher
Experience with AI models

Education: PhD preferred in computer science, maths, physics, engineering or a similar field
Experience: 5+ years as a model developer or data researcher preferred
Languages and tools: Python
TensorFlow
PyTorch
NumPy
Pandas

How to prepare

Build a validation checklist for an ML model covering data, design, performance and monitoring
Practise testing a neural network for robustness to perturbations and distribution shift
Learn model risk guidance such as SR 11-7 and what effective challenge means
Compare a complex model with a simple benchmark and write up the trade-offs

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.