Quant jobs / BNP Paribas

AI Model Validator

Validate AI models used by BNP Paribas Global Markets and related teams. Reviews cover financial research applications alongside language-model workflows and ongoing performance monitoring.

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 independent tests for trading and pricing AI models.
Assess predictive performance, bias and possible misuse.
Review generative-AI workflows and their supporting data.
Present validation conclusions and track ongoing model behaviour.

What they ask for

Required

Financial AI model development or validation
Machine learning and time-series methods
Practical generative-AI experience
Python or R
Technical documentation
French and English

Preferred

Trading-desk knowledge
LangChain or LangGraph
Regulatory model-risk standards

Education: Master’s or PhD in finance, economics, statistics, computing or another quantitative subject.
Experience: At least 3 years developing or validating AI models for quantitative finance.
Languages and tools: Python
R
TensorFlow
PyTorch
NLTK
Gensim
GitHub
Markets: multi-asset

How to prepare

Validate an ML pricing model against a numerical benchmark.
Test a RAG workflow for retrieval errors and unsupported output.
Document performance drift and a proposed monitoring plan.

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

View the posting on BNP Paribas’s site ↗

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