Quant jobs / Citi

Wholesale Credit Risk Model Overlays Officer

A credit risk analytics role that calculates and applies overlays to raw wholesale credit model output, for example for CECL and CCAR. It sits within Citi's portfolio credit risk group and works quarterly.

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.

Analyse quarter-on-quarter model output changes against portfolio and economic shifts
Calculate and document overlays in a repeatable, controlled way
Challenge assumptions not backed by statistical evidence
Prepare approval documents and executive slides
Reconcile data and automate parts of the overlay process

What they ask for

Required

6+ years in risk management
Credit risk concepts and methods
Strong Python
Handling large datasets
Technical documentation
Root cause analysis

Preferred

Wholesale CCAR, stress testing or CECL experience
Other programming languages

Education: No degree level stated
Experience: 6+ years in risk management or a related function
Languages and tools: Python
Markets: credit

How to prepare

Learn how CECL and CCAR use model output and where management overlays come in
Build a Python workflow that explains period-on-period loss changes by driver
Practise documenting a calculation so someone else can reproduce it
Study credit risk concepts such as PD, LGD and exposure drivers

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 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.