Quant jobs / BlackRock

Associate, AI Model Validation – Risk & Quantitative Analysis

An independent validation role in BlackRock's enterprise risk group, reviewing AI tools, agents and RAG systems used in business workflows. It applies model-risk thinking to generative AI.

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.

Design validation plans and test cases for AI use cases
Test accuracy, guardrails, robustness and monitoring of LLM systems
Review data quality and preprocessing choices
Run security tests such as prompt injection checks
Report findings and escalate gaps to senior risk committees

What they ask for

Required

3-7 years in IT or financial services
Degree in computer science, data science, statistics or maths
LLMs, RAG and agentic systems
Python with PyTorch or TensorFlow
Evaluation and benchmark design
Written communication

Preferred

AI observability and monitoring
Responsible AI (fairness, explainability)
Fine-tuning
AI security testing

Education: Degree or advanced degree (MS, PhD) in computer science, data science, statistics, applied maths or related
Experience: 3-7 years in IT or financial industry
Languages and tools: Python
PyTorch
TensorFlow

How to prepare

Build a small RAG app and write an evaluation suite for it
Learn LLM evaluation methods and ground-truth creation
Test the app for prompt injection and data leakage
Study model risk guidance such as SR 11/7 for AI
Write a validation report on your own app

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 BlackRock’s site before applying: requirements, location and pay can change after we check them.

View the posting on BlackRock’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with BlackRock and doesn’t handle applications.