Quant jobs / BNP Paribas

Transversal Quantitative Analyst

Build shared quantitative tools for BNP Paribas’s risk modelling and simulation teams. The position focuses on reusable code, process automation and consistent implementation across groups.

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 tools used for modelling, simulation and stress tests.
Automate common quantitative workflows.
Standardise shared code and improve traceability of results.
Evaluate AI-assisted analysis and quality controls with modelling teams.

What they ask for

Required

Quantitative risk or simulation background
Programming ability
Understanding of model production lifecycles
Reusable tool design
Cross-team communication

Education: Academic training in a subject such as engineering, statistics, quantitative finance or mathematics; degree level not stated.
Experience: Up to 3 years in quantitative, modelling or analytical work.
Languages and tools: Python
SQL
VBA

How to prepare

Build a reusable stress-testing pipeline with clear inputs and outputs.
Add reproducible checks and traceability to simulation results.
Refactor duplicated modelling routines into shared functions.

What to study

The Risk 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.