Quant jobs / BNP Paribas

Model Validator, Compliance

Independently test financial-crime and compliance models within the bank’s model risk function. The role challenges statistical assumptions and explains model weaknesses to decision-makers.

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.

Develop validation plans for AML, fraud or sanctions models.
Test predictive behaviour and assess whether outputs are fit for use.
Challenge model assumptions and vendor evidence.
Write technical findings and present unresolved risks.

What they ask for

Required

Compliance-model development or validation
Statistics and probability
AI and machine-learning assessment
Python or R
Technical reporting

Education: Master’s or PhD in statistics, computing, finance, economics or a quantitative subject.
Experience: At least 2 years developing or validating AML, fraud, sanctions or financial-crime models.
Languages and tools: Python
R

How to prepare

Validate a classification model with imbalance-aware metrics.
Test calibration and sensitivity across customer segments.
Write a model challenge report separating evidence from assumptions.

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.