Quant jobs / Citi

Wholesale Credit Reserves & Loss Modelling – Quantitative Analyst

A modelling role in Citi's risk data and analytics group, in the team building credit loss models for reserves (IFRS9, CECL) and stress tests (ICAAP, CCAR). It supports risk managers, model validation and regulators.

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.

Build and test wholesale expected credit loss models for IFRS9 and stress testing
Implement models in Citi's internal Python library
Prepare analysis for risk managers and senior management
Support model validation, audit and regulator discussions

What they ask for

Required

Master's in a quantitative field
3+ years in quantitative financial modelling
Applying advanced maths to real problems
Statistics packages and regression
Strong Python
Communication skills

Preferred

Wholesale credit products knowledge
IFRS9/CECL, ICAAP/CCAR or PD/LGD/EAD modelling
Linux

Education: Master's in a quantitative field such as maths, physics, computer science, econometrics, statistics, economics or finance
Experience: 3+ years in quantitative financial modelling
Languages and tools: Python
Markets: credit

How to prepare

Build PD, LGD and EAD models in Python on public credit data
Study IFRS9 staging and expected credit loss calculation
Learn how stress testing links macro scenarios to losses
Practise regression diagnostics and model documentation

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

View the posting on Citi’s site ↗

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